* using log directory 'd:/Rcompile/CRANpkg/local/3.3/sm.Rcheck'
* using R version 3.3.3 (2017-03-06)
* using platform: x86_64-w64-mingw32 (64-bit)
* using session charset: ISO8859-1
* checking for file 'sm/DESCRIPTION' ... OK
* checking extension type ... Package
* this is package 'sm' version '2.2-5.4'
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking whether package 'sm' can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking R files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* loading checks for arch 'i386'
** checking whether the package can be loaded ... OK
** checking whether the package can be loaded with stated dependencies ... OK
** checking whether the package can be unloaded cleanly ... OK
** checking whether the namespace can be loaded with stated dependencies ... OK
** checking whether the namespace can be unloaded cleanly ... OK
** checking loading without being on the library search path ... OK
** checking use of S3 registration ... OK
* loading checks for arch 'x64'
** checking whether the package can be loaded ... OK
** checking whether the package can be loaded with stated dependencies ... OK
** checking whether the package can be unloaded cleanly ... OK
** checking whether the namespace can be loaded with stated dependencies ... OK
** checking whether the namespace can be unloaded cleanly ... OK
** checking loading without being on the library search path ... OK
** checking use of S3 registration ... OK
* checking dependencies in R code ... NOTE
'library' or 'require' calls in package code:
  'akima' 'misc3d' 'rgl' 'rpanel' 'tkrplot'
  Please use :: or requireNamespace() instead.
  See section 'Suggested packages' in the 'Writing R Extensions' manual.
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... NOTE
addplot: no visible global function definition for 'par'
addplot: no visible global function definition for 'points'
britmap: no visible binding for global variable 'britpts'
britmap: no visible global function definition for 'lines'
circle: no visible global function definition for 'par'
circle: no visible global function definition for 'lines'
cv: no visible global function definition for 'dnorm'
cv: no visible global function definition for 'var'
cv.crit.dens: no visible global function definition for 'dnorm'
h.select: no visible global function definition for 'var'
h.select: no visible global function definition for 'optim'
h.select: no visible global function definition for 'optimise'
hcv: no visible global function definition for 'var'
hcv: no visible global function definition for 'plot'
hcv: no visible global function definition for 'lines'
hidplot: no visible global function definition for 'par'
hidplot: no visible global function definition for 'points'
lambda.select: no visible global function definition for 'uniroot'
latlines: no visible global function definition for 'par'
latlines: no visible global function definition for 'points'
latlines.e: no visible global function definition for 'par'
latlines.e: no visible global function definition for 'points'
longlines: no visible global function definition for 'par'
longlines: no visible global function definition for 'points'
longlines.e: no visible global function definition for 'par'
longlines.e: no visible global function definition for 'points'
nise: no visible global function definition for 'dnorm'
nmise: no visible global function definition for 'dnorm'
nnbr: no visible global function definition for 'var'
normdens.band: no visible global function definition for 'dnorm'
normdens.band: no visible global function definition for 'par'
normdens.band: no visible global function definition for 'polygon'
p.quad.moment: no visible global function definition for 'pchisq'
p.quad.moment.adjusted: no visible global function definition for
  'pchisq'
p.quad.moment.old: no visible global function definition for 'pchisq'
plot.density2: no visible global function definition for 'rgl.pop'
plot.density3: no visible global function definition for 'pop3d'
plot.smooth2: no visible global function definition for 'rgl.pop'
plot2: no visible global function definition for 'par'
plot2: no visible global function definition for 'points'
plot2: no visible global function definition for 'text'
plot2d: no visible global function definition for 'par'
plot2d: no visible global function definition for 'plot'
ps.normal: no visible global function definition for 'uniroot'
ps.normal: no visible global function definition for 'plot'
ps.normal: no visible global function definition for 'lines'
ps.normal: no visible global function definition for 'persp'
replot.density1: no visible global function definition for
  'rp.tkrreplot'
replot.density1: no visible binding for global variable 'plot'
replot.density2: no visible global function definition for
  'rp.tkrreplot'
replot.density3: no visible global function definition for
  'rp.tkrreplot'
replot.smooth1: no visible global function definition for
  'rp.tkrreplot'
replot.smooth1: no visible binding for global variable 'plot'
replot.smooth2: no visible global function definition for
  'rp.tkrreplot'
rp.colour.chart: no visible global function definition for 'plot'
rp.colour.chart: no visible global function definition for 'axis'
rp.colour.chart: no visible global function definition for 'rect'
rp.colour.chart: no visible global function definition for 'box'
rp.density1: no visible global function definition for 'rp.control'
rp.density1: no visible global function definition for 'rp.tkrplot'
rp.density1: no visible binding for global variable 'plot'
rp.density1: no visible global function definition for 'rp.radiogroup'
rp.density1: no visible global function definition for 'rp.slider'
rp.density1: no visible global function definition for 'rp.checkbox'
rp.density1: no visible global function definition for 'rp.do'
rp.density2: no visible global function definition for 'rp.control'
rp.density2: no visible global function definition for 'rp.tkrplot'
rp.density2: no visible global function definition for 'rp.radiogroup'
rp.density2: no visible global function definition for 'rp.slider'
rp.density3: no visible global function definition for 'rp.control'
rp.density3: no visible global function definition for 'rp.tkrplot'
rp.density3: no visible global function definition for 'rp.radiogroup'
rp.density3: no visible global function definition for 'rp.slider'
rp.smooth1: no visible global function definition for 'rp.control'
rp.smooth1: no visible global function definition for 'rp.tkrplot'
rp.smooth1: no visible binding for global variable 'plot'
rp.smooth1: no visible global function definition for 'rp.radiogroup'
rp.smooth1: no visible global function definition for 'rp.slider'
rp.smooth1: no visible global function definition for 'rp.checkbox'
rp.smooth1: no visible global function definition for 'rp.do'
rp.smooth2: no visible global function definition for 'rp.control'
rp.smooth2: no visible global function definition for 'rp.tkrplot'
rp.smooth2: no visible global function definition for 'rp.radiogroup'
rp.smooth2: no visible global function definition for 'rp.slider'
rp.smooth2: no visible global function definition for 'rp.checkbox'
set.bandwidth: no visible global function definition for 'rp.do'
set.bandwidth.d: no visible global function definition for 'rp.do'
sig.trace: no visible global function definition for 'plot'
sig.trace: no visible global function definition for 'lines'
sj : phi6: no visible global function definition for 'dnorm'
sj : phi4: no visible global function definition for 'dnorm'
sj: no visible global function definition for 'quantile'
sj: no visible global function definition for 'dnorm'
sm: no visible global function definition for 'terms'
sm: no visible global function definition for 'as.formula'
sm: no visible global function definition for 'model.matrix'
sm: no visible global function definition for 'approxfun'
sm : sm.pam.draw: no visible global function definition for 'plot'
sm : sm.pam.draw: no visible global function definition for 'title'
sm : sm.pam.redraw: no visible global function definition for
  'rp.tkrreplot'
sm : sm.pam.redraw: no visible binding for global variable 'plot'
sm: no visible global function definition for 'rp.control'
sm: no visible global function definition for 'rp.tkrplot'
sm: no visible binding for global variable 'plot'
sm: no visible global function definition for 'rp.slider'
sm: no visible global function definition for 'rp.checkbox'
sm: no visible global function definition for 'plot'
sm.ancova: no visible global function definition for 'plot'
sm.ancova: no visible global function definition for 'text'
sm.ancova: no visible global function definition for 'par'
sm.ancova: no visible global function definition for 'polygon'
sm.ancova: no visible global function definition for 'lines'
sm.autoregression : sm.autoregression.1d: no visible global function
  definition for 'plot'
sm.autoregression : sm.autoregression.1d: no visible global function
  definition for 'lines'
sm.autoregression : sm.autoregression.1d: no visible global function
  definition for 'acf'
sm.autoregression : sm.autoregression.1d: no visible global function
  definition for 'title'
sm.autoregression : sm.autoregression.2d: no visible global function
  definition for 'quantile'
sm.autoregression : sm.autoregression.2d: no visible global function
  definition for 'persp'
sm.autoregression : sm.autoregression.2d: no visible global function
  definition for 'title'
sm.binomial: no visible binding for global variable 'nobs'
sm.binomial: no visible global function definition for 'plot'
sm.binomial: no visible global function definition for 'abline'
sm.binomial: no visible global function definition for 'points'
sm.binomial: no visible global function definition for 'binomial'
sm.binomial: no visible global function definition for 'lines'
sm.binomial.bootstrap : rbetabinom: no visible global function
  definition for 'rbeta'
sm.binomial.bootstrap : rbetabinom: no visible global function
  definition for 'rbinom'
sm.binomial.bootstrap: no visible global function definition for
  'binomial'
sm.binomial.bootstrap: no visible global function definition for 'poly'
sm.binomial.bootstrap: no visible global function definition for
  'glm.fit'
sm.binomial.bootstrap: no visible global function definition for
  'fitted'
sm.binomial.bootstrap: no visible global function definition for
  'residuals'
sm.binomial.bootstrap: no visible global function definition for
  'lines'
sm.check.data: no visible global function definition for 'na.omit'
sm.density.1d: no visible global function definition for 'quantile'
sm.density.1d: no visible global function definition for 'plot'
sm.density.1d: no visible global function definition for 'dnorm'
sm.density.2d: no visible global function definition for 'dnorm'
sm.density.3d: no visible global function definition for 'topo.colors'
sm.density.compare: no visible global function definition for 'plot'
sm.density.compare: no visible global function definition for 'lines'
sm.density.compare: no visible global function definition for 'polygon'
sm.density.eval.3d: no visible global function definition for
  'quantile'
sm.density.eval.3d: no visible global function definition for
  'contour3d'
sm.density.eval.3d: no visible global function definition for
  'rp.plot3d'
sm.density.eval.3d: no visible global function definition for
  'triangles3d'
sm.discontinuity: no visible binding for global variable 'df'
sm.discontinuity.1d: no visible global function definition for 'plot'
sm.discontinuity.1d: no visible global function definition for
  'polygon'
sm.discontinuity.1d: no visible global function definition for 'lines'
sm.discontinuity.1d: no visible global function definition for 'points'
sm.discontinuity.2d: no visible global function definition for 'chull'
sm.discontinuity.2d: no visible global function definition for 'plot'
sm.discontinuity.2d: no visible global function definition for
  'contour'
sm.glm: no visible global function definition for 'glm.fit'
sm.imageplot: no visible global function definition for 'image'
sm.mask: no visible global function definition for 'chull'
sm.monotonicity: no visible binding for global variable 'df'
sm.monotonicity: no visible global function definition for 'var'
sm.monotonicity: no visible global function definition for 'plot'
sm.monotonicity: no visible global function definition for 'rbinom'
sm.monotonicity: no visible global function definition for 'lines'
sm.pam.colour.chart: no visible global function definition for 'par'
sm.pca : <anonymous>: no visible global function definition for
  'quantile'
sm.pca: no visible global function definition for 'plot'
sm.pca: no visible global function definition for 'polygon'
sm.pca: no visible global function definition for 'lines'
sm.pca: no visible global function definition for 'col2rgb'
sm.pca: no visible global function definition for 'rgb'
sm.pca: no visible global function definition for 'segments'
sm.pca: no visible binding for global variable 'sd'
sm.persplot: no visible global function definition for 'persp'
sm.poisson: no visible global function definition for 'plot'
sm.poisson: no visible global function definition for 'points'
sm.poisson: no visible global function definition for 'poisson'
sm.poisson: no visible global function definition for 'lines'
sm.poisson.bootstrap : rNegBin: no visible global function definition
  for 'rgamma'
sm.poisson.bootstrap : rNegBin: no visible global function definition
  for 'rpois'
sm.poisson.bootstrap: no visible global function definition for
  'poisson'
sm.poisson.bootstrap: no visible global function definition for 'poly'
sm.poisson.bootstrap: no visible global function definition for
  'glm.fit'
sm.poisson.bootstrap: no visible global function definition for
  'fitted'
sm.poisson.bootstrap: no visible global function definition for 'lines'
sm.regression.1d: no visible global function definition for 'plot'
sm.regression.2d: no visible global function definition for 'rainbow'
sm.regression.2d: no visible global function definition for 'image'
sm.regression.2d: no visible global function definition for 'contour'
sm.regression.2d: no visible global function definition for 'persp'
sm.regression.2d: no visible global function definition for 'rp.plot3d'
sm.regression.autocor: no visible global function definition for 'plot'
sm.regression.autocor: no visible global function definition for
  'title'
sm.regression.autocor: no visible global function definition for
  'lines'
sm.regression.eval.2d: no visible global function definition for
  'chull'
sm.rglplot: no visible global function definition for 'rp.plot3d'
sm.rm: no visible global function definition for 'plot'
sm.rm: no visible global function definition for 'title'
sm.rm: no visible global function definition for 'lines'
sm.rm: no visible global function definition for 'optim'
sm.sigma2: no visible global function definition for 'chull'
sm.sigma2: no visible global function definition for 'var'
sm.sigma2: no visible global function definition for 'contour'
sm.sigma2: no visible global function definition for 'qchisq'
sm.sigweight: no visible global function definition for 'var'
sm.sliceplot: no visible global function definition for 'plot'
sm.sliceplot: no visible global function definition for 'points'
sm.sliceplot: no visible global function definition for 'quantile'
sm.sliceplot: no visible global function definition for 'contour'
sm.sphere: no visible global function definition for 'menu'
sm.sphere: no visible global function definition for 'par'
sm.surface3d: no visible global function definition for 'triangles3d'
sm.surface3d: no visible global function definition for 'segments3d'
sm.survival: no visible global function definition for 'plot'
sm.survival: no visible global function definition for 'text'
sm.survival: no visible global function definition for 'lines'
sm.ts.pdf: no visible global function definition for 'title'
sm.variogram: no visible binding for global variable 'df'
sm.variogram: no visible global function definition for 'var'
sm.variogram: no visible global function definition for 'plot'
sm.variogram: no visible global function definition for 'polygon'
sm.variogram: no visible global function definition for 'points'
sm.variogram: no visible global function definition for 'segments'
sm.variogram: no visible global function definition for 'lines'
sm.variogram: no visible global function definition for 'interp'
sm.variogram: no visible global function definition for 'contourLines'
sm.variogram: no visible global function definition for
  'filled.contour'
sm.variogram: no visible binding for global variable 'topo.colors'
sm.variogram: no visible global function definition for 'axis'
sm.variogram: no visible global function definition for 'contour'
smplot.density: no visible global function definition for 'polygon'
smplot.density: no visible global function definition for 'par'
smplot.density: no visible global function definition for 'box'
smplot.density: no visible global function definition for 'lines'
smplot.density: no visible global function definition for 'rug'
smplot.density: no visible global function definition for 'dnorm'
smplot.regression: no visible global function definition for 'par'
smplot.regression: no visible global function definition for 'polygon'
smplot.regression: no visible global function definition for 'lines'
smplot.regression: no visible global function definition for 'points'
smplot.regression: no visible global function definition for 'box'
sphimage: no visible global function definition for 'image'
sphimage: no visible global function definition for 'polygon'
Undefined global functions or variables:
  abline acf approxfun as.formula axis binomial box britpts chull
  col2rgb contour contour3d contourLines df dnorm filled.contour fitted
  glm.fit image interp lines menu model.matrix na.omit nobs optim
  optimise par pchisq persp plot points poisson poly polygon pop3d
  qchisq quantile rainbow rbeta rbinom rect residuals rgamma rgb
  rgl.pop rp.checkbox rp.control rp.do rp.plot3d rp.radiogroup
  rp.slider rp.tkrplot rp.tkrreplot rpois rug sd segments segments3d
  terms text title topo.colors triangles3d uniroot var
Consider adding
  importFrom("grDevices", "chull", "col2rgb", "contourLines", "rainbow",
             "rgb", "topo.colors")
  importFrom("graphics", "abline", "axis", "box", "contour",
             "filled.contour", "image", "lines", "par", "persp", "plot",
             "points", "polygon", "rect", "rug", "segments", "text",
             "title")
  importFrom("stats", "acf", "approxfun", "as.formula", "binomial", "df",
             "dnorm", "fitted", "glm.fit", "model.matrix", "na.omit",
             "nobs", "optim", "optimise", "pchisq", "poisson", "poly",
             "qchisq", "quantile", "rbeta", "rbinom", "residuals",
             "rgamma", "rpois", "sd", "terms", "uniroot", "var")
  importFrom("utils", "menu")
to your NAMESPACE file.
* checking Rd files ... OK
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of 'data' directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking line endings in C/C++/Fortran sources/headers ... OK
* checking compiled code ... OK
* checking examples ...
** running examples for arch 'i386' ... [24s] OK
** running examples for arch 'x64' ... [24s] OK
* checking for unstated dependencies in 'tests' ... OK
* checking tests ...
** running tests for arch 'i386' ... [27s] ERROR
  Running 'test_scripts.R' [26s]
Running the tests in 'tests/test_scripts.R' failed.
Complete output:
  > ## Note: R CMD check may run these scripts from an installed package
  > scripts <- list.files(system.file("scripts", package = "sm"), ".*\\.q$")
  > ## these are interactive
  > omit2 <- match(c("bissell3.q", "dogs.q"), scripts)
  > scripts <- scripts[-omit2]
  > library(sm)
  Package 'sm', version 2.2-5.4: type help(sm) for summary information
  > if(.Platform$OS.type == "unix") options(pager="cat") else options(pager="console")
  > postscript(file="test_scripts.ps")
  > for(z in scripts) {
  +     cat("\n============ running script `", z, "' ============\n", sep="")
  +     set.seed(123)
  +     source(system.file("scripts", z, package = "sm"), echo=TRUE)
  +     rm(list = ls(all = TRUE))
  + }
  
  ============ running script `air_band.q' ============
  
  > with(aircraft, {
  +     y <- log(Span)[Period == 3]
  +     sm.density(y, xlab = "Log span", display = "se")
  + })
  
  ============ running script `air_boot.q' ============
  
  > with(aircraft, {
  +     y <- log(Span)[Period == 3]
  +     sm.density(y, xlab = "Log span")
  +     for (i in 1:20) sm.density(sample(y, replace = TRUE) .... [TRUNCATED] 
  
  ============ running script `air_cont.q' ============
  
  > with(airpc, {
  +     pc <- cbind(Comp.1, Comp.2)
  +     pc1 <- pc[Period == 1, ]
  +     pc2 <- pc[Period == 2, ]
  +     pc3 <- pc[Period == 3, ]
  +     p .... [TRUNCATED] 
  Loading required package: rgl
  Loading required package: rpanel
  Loading required package: tcltk
  Package `rpanel', version 1.1-3: type help(rpanel) for summary information
  
  ============ running script `air_dens.q' ============
  
  > with(airpc, {
  +     pc3 <- cbind(Comp.1, Comp.2)[Period == 3, ]
  +     par(mfrow = c(2, 2))
  +     par(cex = 0.6)
  +     plot(pc3)
  +     sm.density(pc3 .... [TRUNCATED] 
  
  ============ running script `air_hcv.q' ============
  
  > with(aircraft, {
  +     y <- log(Span)[Period == 3]
  +     par(mfrow = c(1, 2))
  +     sm.density(y, h = hcv(y), xlab = "Log span", lty = 3, yht = 1.4) .... [TRUNCATED] 
  
  ============ running script `air_imag.q' ============
  
  > with(airpc, {
  +     pc3 <- cbind(Comp.1, Comp.2)[Period == 3, ]
  +     par(mfrow = c(1, 2))
  +     sm.density(pc3, display = "image")
  +     sm.density .... [TRUNCATED] 
  
  ============ running script `air_ind.q' ============
  
  > with(aircraft, {
  +     Speed3 <- log(Speed[Period == 3])
  +     Span3 <- log(Span[Period == 3])
  +     par(mfrow = c(1, 2))
  +     plot(Span3, Speed3,  .... [TRUNCATED] 
  
  ============ running script `air_inds.q' ============
  
  > with(aircraft, {
  +     Speed3 <- log(Speed[Period == 3])
  +     Span3 <- log(Span[Period == 3])
  +     air3 <- cbind(Span3, Speed3)
  +     result.12 <- .... [TRUNCATED] 
  Observed value:  -0.12786 
  1  2  3  4  5  6  7  8  9  10  11  12  13  14  15  16  17  18  19  20  21  22  23  24  25  26  27  28  29  30  31  32  33  34  35  36  37  38  39  40  41  42  43  44  45  46  47  48  49  50  51  52  53  54  55  56  57  58  59  60  61  62  63  64  65  66  67  68  69  70  71  72  73  74  75  76  77  78  79  80  81  82  83  84  85  86  87  88  89  90  91  92  93  94  95  96  97  98  99  100  101  102  103  104  105  106  107  108  109  110  111  112  113  114  115  116  117  118  119  120  121  122  123  124  125  126  127  128  129  130  131  132  133  134  135  136  137  138  139  140  141  142  143  144  145  146  147  148  149  150  151  152  153  154  155  156  157  158  159  160  161  162  163  164  165  166  167  168  169  170  171  172  173  174  175  176  177  178  179  180  181  182  183  184  185  186  187  188  189  190  191  192  193  194  195  196  197  198  199  200  Empirical significance: 1 
  
  ============ running script `air_scat.q' ============
  
  > with(airpc, {
  +     pc <- cbind(Comp.1, Comp.2)
  +     pc1 <- pc[Period == 1, ]
  +     pc2 <- pc[Period == 2, ]
  +     pc3 <- pc[Period == 3, ]
  +     x .... [TRUNCATED] 
  
  ============ running script `bin_use.q' ============
  
  > cat("Examples of use of function binning()\n")
  Examples of use of function binning()
  
  > x <- rnorm(1000)
  
  > xb <- binning(x)
  
  > h <- hnorm(x)
  
  > sm.density(xb$x, h = h, weights = xb$x.freq, ylim = c(0, 
  +     0.5/sqrt(var(x))))
  
  > pause()
  
  > x <- cbind(x, x + rnorm(1000))
  
  > xb <- binning(x)
  
  > h <- hnorm(x)
  
  > par(mfrow = c(1, 2))
  
  > sm.density(xb$x, h = h, weights = xb$x.freq)
  
  > sm.density(xb$x, h = h, weights = xb$x.freq, display = "slice")
  
  > par(mfrow = c(1, 1))
  
  > pause()
  
  > with(airpc, {
  +     pc3 <- cbind(Comp.1, Comp.2)[Period == 3, ]
  +     pc.bin <- binning(pc3)
  +     par(mfrow = c(1, 2))
  +     sm.density(pc.bin$x, h .... [TRUNCATED] 
  this time original data rather than grid data are plotted
  
  ============ running script `birth1.q' ============
  
  > with(birth, {
  +     Low1 <- Low[Smoke == "S"]
  +     Lwt1 <- Lwt[Smoke == "S"]
  +     Lj <- jitter(Low1, amount = 0)
  +     plot(Lwt1, Lj, type = "n",  .... [TRUNCATED] 
  
  ============ running script `birth2.q' ============
  
  > with(birth, {
  +     Low0 <- Low[Smoke == "N"]
  +     Lwt0 <- Lwt[Smoke == "N"]
  +     Low1 <- Low[Smoke == "S"]
  +     Lwt1 <- Lwt[Smoke == "S"]
  +      .... [TRUNCATED] 
  
  ============ running script `bissell1.q' ============
  
  > with(bissell, {
  +     plot(Length, Flaws, xlim = c(0, 1000), pch = "o")
  +     beta <- sum(Flaws)/sum(Length)
  +     x <- seq(0, 1000, length = 50)
  +  .... [TRUNCATED] 
  
  ============ running script `bissell2.q' ============
  
  > with(bissell, {
  +     plot(Length, Flaws, xlim = c(0, 1000), pch = "o")
  +     beta <- sum(Flaws)/sum(Length)
  +     x <- seq(0, 1000, length = 50)
  +  .... [TRUNCATED] 
  
  ============ running script `citrate.q' ============
  
  > with(citrate, {
  +     Citrate <- as.matrix(citrate)
  +     nSubj <- dim(Citrate)[1]
  +     nTime <- dim(Citrate)[2]
  +     Time <- (1:nTime)
  +     plot .... [TRUNCATED] 
  Autocovariances & autocorrelations:
       auto-cov  auto-corr
  0  360.623571 1.00000000
  1  244.287143 0.67740204
  2  204.040714 0.56579972
  3  175.807857 0.48751072
  4  151.130000 0.41907965
  5  128.680714 0.35682835
  6  120.196429 0.33330164
  7  103.723571 0.28762283
  8   91.565000 0.25390742
  9   87.847857 0.24359988
  10  53.901429 0.14946729
  11  22.932143 0.06359025
  12  13.760714 0.03815811
  13   9.732143 0.02698698
         Rice's criterion:
         h    indept.   depend.
  [1] 0.100000 6.005194 6.005194
  [1] 0.200000 6.005156 6.005182
  [1] 0.300000 5.965648 5.992517
  [1] 0.400000 5.583011 5.878175
  [1] 0.500000 4.855846 5.702201
  [1] 0.600000 4.131101 5.579386
  [1] 0.700000 3.535247 5.519406
  [1] 0.800000 3.072755 5.506906
  [1] 0.900000 2.735846 5.530976
  [1] 1.000000 2.516341 5.582579
  [1] 1.100000 2.400934 5.653475
  [1] 1.200000 2.370399 5.736703
  [1] 1.300000 2.402966 5.826924
  [1] 1.400000 2.478570 5.920349
  [1] 1.500000 2.581237 6.014418
  [1] 1.600000 2.699336 6.107412
  [1] 1.700000 2.824778 6.198149
  [1] 1.800000 2.952046 6.285777
  [1] 1.900000 3.077424 6.369671
  [1] 2.000000 3.198465 6.449387
  h:  0.8 
  
  ============ running script `edfgrad.q' ============
  
  > with(aircraft, {
  +     y <- log(Span[Period == 3])
  +     n <- length(y)
  +     plot(sort(y), (1:n)/n, type = "S", xlab = "y", ylab = "Empirical distr ..." ... [TRUNCATED] 
  
  ============ running script `follicle.q' ============
  
  > with(follicle, {
  +     sm.regression(Age, log(Count), h = 4, lty = 2)
  +     model <- loess(log(Count) ~ Age)
  +     lines(Age, model$fitted, col = 6) .... [TRUNCATED] 
  
  ============ running script `geys3d.q' ============
  
  > with(geys3d, {
  +     par(mfrow = c(1, 2))
  +     plot(Waiting, Duration)
  +     sm.density(geys3d)
  +     par(mfrow = c(1, 1))
  + })
  Loading required package: misc3d
  
  ============ running script `geys_ts.q' ============
  
  > d <- geyser$duration
  
  > cat("Data are: d=(duration of geyser eruption)\n")
  Data are: d=(duration of geyser eruption)
  
  > cat("Marginal density of d(t) first, followed by\n")
  Marginal density of d(t) first, followed by
  
  > cat("estimated density of (d(t-k),d(t)), for k=1,2\n")
  estimated density of (d(t-k),d(t)), for k=1,2
  
  > a <- sm.ts.pdf(d, lags = c(1, 2))
  
  ============ running script `lc_comp.q' ============
  
  > with(lcancer, {
  +     cases <- cbind(Easting/10000, Northing/10000)[Cancer == 1, 
  +         ]
  +     controls <- cbind(Easting/10000, Northing/10000) .... [TRUNCATED] 
  Observed value: 384.6738 
  1  2  3  4  5  6  7  8  9  10  11  12  13  14  15  16  17  18  19  20  
  p-value =  0.75 
  
  ============ running script `lc_dens.q' ============
  
  > with(lcancer, {
  +     cases <- cbind(Easting, Northing)[Cancer == 1, ]/10000
  +     controls <- cbind(Easting, Northing)[Cancer == 2, ]/10000
  +     x .... [TRUNCATED] 
  
  ============ running script `lc_rr.q' ============
  
  > with(lcancer, {
  +     cases <- cbind(Easting, Northing)[Cancer == 1, ]/10000
  +     controls <- cbind(Easting, Northing)[Cancer == 2, ]/10000
  +     x .... [TRUNCATED] 
  
  ============ running script `lynx.q' ============
  
  > ts.plot(lynx)
  
  > title("Canadian lynx trapping (1821-1934)")
  
  > pause()
  
  > cat("Data are now log-transformed\n")
  Data are now log-transformed
  
  > log.lynx <- log(lynx)
  
  > sm.ts.pdf(log.lynx, lags = 4:5)
  
  > pause()
  
  > sm.autoregression(log.lynx, maxlag = 5, se = TRUE)
  
  > pause()
  
  > sm.autoregression(log.lynx, lags = cbind(4, 5))
  
  ============ running script `mackgam.q' ============
  
  > library(gam)
  Loading required package: splines
  Loading required package: foreach
  Loaded gam 1.15
  
  
  > model1 <- gam(log(Density) ~ lo(log(mack.depth)) + 
  +     lo(Temperature) + lo(mack.lat, mack.long), data = mackerel)
  
  > print(model1)
  Call:
  gam(formula = log(Density) ~ lo(log(mack.depth)) + lo(Temperature) + 
      lo(mack.lat, mack.long), data = mackerel)
  
  Degrees of Freedom: 278 total; 262.7774 Residual
  Residual Deviance: 260.3544 
  
  > print(gam(log(Density) ~ lo(Temperature) + lo(mack.lat, 
  +     mack.long), data = mackerel))
  Call:
  gam(formula = log(Density) ~ lo(Temperature) + lo(mack.lat, mack.long), 
      data = mackerel)
  
  Degrees of Freedom: 278 total; 266.4857 Residual
  Residual Deviance: 359.4476 
  
  > print(gam(log(Density) ~ lo(log(mack.depth)) + lo(mack.lat, 
  +     mack.long), data = mackerel))
  Call:
  gam(formula = log(Density) ~ lo(log(mack.depth)) + lo(mack.lat, 
      mack.long), data = mackerel)
  
  Degrees of Freedom: 278 total; 266.0766 Residual
  Residual Deviance: 271.311 
  
  > print(gam(log(Density) ~ lo(log(mack.depth)) + lo(Temperature), 
  +     data = mackerel))
  Call:
  gam(formula = log(Density) ~ lo(log(mack.depth)) + lo(Temperature), 
      data = mackerel)
  
  Degrees of Freedom: 278 total; 270.9924 Residual
  Residual Deviance: 335.5316 
  
  > par(mfrow = c(2, 2))
  
  > plot.gam(model1, se = TRUE)
  Error in eval(expr, envir, enclos) : could not find function "plot.gam"
  Calls: source -> withVisible -> eval -> eval
  Execution halted
** running tests for arch 'x64' ... [27s] ERROR
  Running 'test_scripts.R' [26s]
Running the tests in 'tests/test_scripts.R' failed.
Complete output:
  > ## Note: R CMD check may run these scripts from an installed package
  > scripts <- list.files(system.file("scripts", package = "sm"), ".*\\.q$")
  > ## these are interactive
  > omit2 <- match(c("bissell3.q", "dogs.q"), scripts)
  > scripts <- scripts[-omit2]
  > library(sm)
  Package 'sm', version 2.2-5.4: type help(sm) for summary information
  > if(.Platform$OS.type == "unix") options(pager="cat") else options(pager="console")
  > postscript(file="test_scripts.ps")
  > for(z in scripts) {
  +     cat("\n============ running script `", z, "' ============\n", sep="")
  +     set.seed(123)
  +     source(system.file("scripts", z, package = "sm"), echo=TRUE)
  +     rm(list = ls(all = TRUE))
  + }
  
  ============ running script `air_band.q' ============
  
  > with(aircraft, {
  +     y <- log(Span)[Period == 3]
  +     sm.density(y, xlab = "Log span", display = "se")
  + })
  
  ============ running script `air_boot.q' ============
  
  > with(aircraft, {
  +     y <- log(Span)[Period == 3]
  +     sm.density(y, xlab = "Log span")
  +     for (i in 1:20) sm.density(sample(y, replace = TRUE) .... [TRUNCATED] 
  
  ============ running script `air_cont.q' ============
  
  > with(airpc, {
  +     pc <- cbind(Comp.1, Comp.2)
  +     pc1 <- pc[Period == 1, ]
  +     pc2 <- pc[Period == 2, ]
  +     pc3 <- pc[Period == 3, ]
  +     p .... [TRUNCATED] 
  Loading required package: rgl
  Loading required package: rpanel
  Loading required package: tcltk
  Package `rpanel', version 1.1-3: type help(rpanel) for summary information
  
  ============ running script `air_dens.q' ============
  
  > with(airpc, {
  +     pc3 <- cbind(Comp.1, Comp.2)[Period == 3, ]
  +     par(mfrow = c(2, 2))
  +     par(cex = 0.6)
  +     plot(pc3)
  +     sm.density(pc3 .... [TRUNCATED] 
  
  ============ running script `air_hcv.q' ============
  
  > with(aircraft, {
  +     y <- log(Span)[Period == 3]
  +     par(mfrow = c(1, 2))
  +     sm.density(y, h = hcv(y), xlab = "Log span", lty = 3, yht = 1.4) .... [TRUNCATED] 
  
  ============ running script `air_imag.q' ============
  
  > with(airpc, {
  +     pc3 <- cbind(Comp.1, Comp.2)[Period == 3, ]
  +     par(mfrow = c(1, 2))
  +     sm.density(pc3, display = "image")
  +     sm.density .... [TRUNCATED] 
  
  ============ running script `air_ind.q' ============
  
  > with(aircraft, {
  +     Speed3 <- log(Speed[Period == 3])
  +     Span3 <- log(Span[Period == 3])
  +     par(mfrow = c(1, 2))
  +     plot(Span3, Speed3,  .... [TRUNCATED] 
  
  ============ running script `air_inds.q' ============
  
  > with(aircraft, {
  +     Speed3 <- log(Speed[Period == 3])
  +     Span3 <- log(Span[Period == 3])
  +     air3 <- cbind(Span3, Speed3)
  +     result.12 <- .... [TRUNCATED] 
  Observed value:  -0.12786 
  1  2  3  4  5  6  7  8  9  10  11  12  13  14  15  16  17  18  19  20  21  22  23  24  25  26  27  28  29  30  31  32  33  34  35  36  37  38  39  40  41  42  43  44  45  46  47  48  49  50  51  52  53  54  55  56  57  58  59  60  61  62  63  64  65  66  67  68  69  70  71  72  73  74  75  76  77  78  79  80  81  82  83  84  85  86  87  88  89  90  91  92  93  94  95  96  97  98  99  100  101  102  103  104  105  106  107  108  109  110  111  112  113  114  115  116  117  118  119  120  121  122  123  124  125  126  127  128  129  130  131  132  133  134  135  136  137  138  139  140  141  142  143  144  145  146  147  148  149  150  151  152  153  154  155  156  157  158  159  160  161  162  163  164  165  166  167  168  169  170  171  172  173  174  175  176  177  178  179  180  181  182  183  184  185  186  187  188  189  190  191  192  193  194  195  196  197  198  199  200  Empirical significance: 1 
  
  ============ running script `air_scat.q' ============
  
  > with(airpc, {
  +     pc <- cbind(Comp.1, Comp.2)
  +     pc1 <- pc[Period == 1, ]
  +     pc2 <- pc[Period == 2, ]
  +     pc3 <- pc[Period == 3, ]
  +     x .... [TRUNCATED] 
  
  ============ running script `bin_use.q' ============
  
  > cat("Examples of use of function binning()\n")
  Examples of use of function binning()
  
  > x <- rnorm(1000)
  
  > xb <- binning(x)
  
  > h <- hnorm(x)
  
  > sm.density(xb$x, h = h, weights = xb$x.freq, ylim = c(0, 
  +     0.5/sqrt(var(x))))
  
  > pause()
  
  > x <- cbind(x, x + rnorm(1000))
  
  > xb <- binning(x)
  
  > h <- hnorm(x)
  
  > par(mfrow = c(1, 2))
  
  > sm.density(xb$x, h = h, weights = xb$x.freq)
  
  > sm.density(xb$x, h = h, weights = xb$x.freq, display = "slice")
  
  > par(mfrow = c(1, 1))
  
  > pause()
  
  > with(airpc, {
  +     pc3 <- cbind(Comp.1, Comp.2)[Period == 3, ]
  +     pc.bin <- binning(pc3)
  +     par(mfrow = c(1, 2))
  +     sm.density(pc.bin$x, h .... [TRUNCATED] 
  this time original data rather than grid data are plotted
  
  ============ running script `birth1.q' ============
  
  > with(birth, {
  +     Low1 <- Low[Smoke == "S"]
  +     Lwt1 <- Lwt[Smoke == "S"]
  +     Lj <- jitter(Low1, amount = 0)
  +     plot(Lwt1, Lj, type = "n",  .... [TRUNCATED] 
  
  ============ running script `birth2.q' ============
  
  > with(birth, {
  +     Low0 <- Low[Smoke == "N"]
  +     Lwt0 <- Lwt[Smoke == "N"]
  +     Low1 <- Low[Smoke == "S"]
  +     Lwt1 <- Lwt[Smoke == "S"]
  +      .... [TRUNCATED] 
  
  ============ running script `bissell1.q' ============
  
  > with(bissell, {
  +     plot(Length, Flaws, xlim = c(0, 1000), pch = "o")
  +     beta <- sum(Flaws)/sum(Length)
  +     x <- seq(0, 1000, length = 50)
  +  .... [TRUNCATED] 
  
  ============ running script `bissell2.q' ============
  
  > with(bissell, {
  +     plot(Length, Flaws, xlim = c(0, 1000), pch = "o")
  +     beta <- sum(Flaws)/sum(Length)
  +     x <- seq(0, 1000, length = 50)
  +  .... [TRUNCATED] 
  
  ============ running script `citrate.q' ============
  
  > with(citrate, {
  +     Citrate <- as.matrix(citrate)
  +     nSubj <- dim(Citrate)[1]
  +     nTime <- dim(Citrate)[2]
  +     Time <- (1:nTime)
  +     plot .... [TRUNCATED] 
  Autocovariances & autocorrelations:
       auto-cov  auto-corr
  0  360.623571 1.00000000
  1  244.287143 0.67740204
  2  204.040714 0.56579972
  3  175.807857 0.48751072
  4  151.130000 0.41907965
  5  128.680714 0.35682835
  6  120.196429 0.33330164
  7  103.723571 0.28762283
  8   91.565000 0.25390742
  9   87.847857 0.24359988
  10  53.901429 0.14946729
  11  22.932143 0.06359025
  12  13.760714 0.03815811
  13   9.732143 0.02698698
         Rice's criterion:
         h    indept.   depend.
  [1] 0.100000 6.005194 6.005194
  [1] 0.200000 6.005156 6.005182
  [1] 0.300000 5.965648 5.992517
  [1] 0.400000 5.583011 5.878175
  [1] 0.500000 4.855846 5.702201
  [1] 0.600000 4.131101 5.579386
  [1] 0.700000 3.535247 5.519406
  [1] 0.800000 3.072755 5.506906
  [1] 0.900000 2.735846 5.530976
  [1] 1.000000 2.516341 5.582579
  [1] 1.100000 2.400934 5.653475
  [1] 1.200000 2.370399 5.736703
  [1] 1.300000 2.402966 5.826924
  [1] 1.400000 2.478570 5.920349
  [1] 1.500000 2.581237 6.014418
  [1] 1.600000 2.699336 6.107412
  [1] 1.700000 2.824778 6.198149
  [1] 1.800000 2.952046 6.285777
  [1] 1.900000 3.077424 6.369671
  [1] 2.000000 3.198465 6.449387
  h:  0.8 
  
  ============ running script `edfgrad.q' ============
  
  > with(aircraft, {
  +     y <- log(Span[Period == 3])
  +     n <- length(y)
  +     plot(sort(y), (1:n)/n, type = "S", xlab = "y", ylab = "Empirical distr ..." ... [TRUNCATED] 
  
  ============ running script `follicle.q' ============
  
  > with(follicle, {
  +     sm.regression(Age, log(Count), h = 4, lty = 2)
  +     model <- loess(log(Count) ~ Age)
  +     lines(Age, model$fitted, col = 6) .... [TRUNCATED] 
  
  ============ running script `geys3d.q' ============
  
  > with(geys3d, {
  +     par(mfrow = c(1, 2))
  +     plot(Waiting, Duration)
  +     sm.density(geys3d)
  +     par(mfrow = c(1, 1))
  + })
  Loading required package: misc3d
  
  ============ running script `geys_ts.q' ============
  
  > d <- geyser$duration
  
  > cat("Data are: d=(duration of geyser eruption)\n")
  Data are: d=(duration of geyser eruption)
  
  > cat("Marginal density of d(t) first, followed by\n")
  Marginal density of d(t) first, followed by
  
  > cat("estimated density of (d(t-k),d(t)), for k=1,2\n")
  estimated density of (d(t-k),d(t)), for k=1,2
  
  > a <- sm.ts.pdf(d, lags = c(1, 2))
  
  ============ running script `lc_comp.q' ============
  
  > with(lcancer, {
  +     cases <- cbind(Easting/10000, Northing/10000)[Cancer == 1, 
  +         ]
  +     controls <- cbind(Easting/10000, Northing/10000) .... [TRUNCATED] 
  Observed value: 384.6738 
  1  2  3  4  5  6  7  8  9  10  11  12  13  14  15  16  17  18  19  20  
  p-value =  0.75 
  
  ============ running script `lc_dens.q' ============
  
  > with(lcancer, {
  +     cases <- cbind(Easting, Northing)[Cancer == 1, ]/10000
  +     controls <- cbind(Easting, Northing)[Cancer == 2, ]/10000
  +     x .... [TRUNCATED] 
  
  ============ running script `lc_rr.q' ============
  
  > with(lcancer, {
  +     cases <- cbind(Easting, Northing)[Cancer == 1, ]/10000
  +     controls <- cbind(Easting, Northing)[Cancer == 2, ]/10000
  +     x .... [TRUNCATED] 
  
  ============ running script `lynx.q' ============
  
  > ts.plot(lynx)
  
  > title("Canadian lynx trapping (1821-1934)")
  
  > pause()
  
  > cat("Data are now log-transformed\n")
  Data are now log-transformed
  
  > log.lynx <- log(lynx)
  
  > sm.ts.pdf(log.lynx, lags = 4:5)
  
  > pause()
  
  > sm.autoregression(log.lynx, maxlag = 5, se = TRUE)
  
  > pause()
  
  > sm.autoregression(log.lynx, lags = cbind(4, 5))
  
  ============ running script `mackgam.q' ============
  
  > library(gam)
  Loading required package: splines
  Loading required package: foreach
  Loaded gam 1.15
  
  
  > model1 <- gam(log(Density) ~ lo(log(mack.depth)) + 
  +     lo(Temperature) + lo(mack.lat, mack.long), data = mackerel)
  
  > print(model1)
  Call:
  gam(formula = log(Density) ~ lo(log(mack.depth)) + lo(Temperature) + 
      lo(mack.lat, mack.long), data = mackerel)
  
  Degrees of Freedom: 278 total; 262.7774 Residual
  Residual Deviance: 260.3544 
  
  > print(gam(log(Density) ~ lo(Temperature) + lo(mack.lat, 
  +     mack.long), data = mackerel))
  Call:
  gam(formula = log(Density) ~ lo(Temperature) + lo(mack.lat, mack.long), 
      data = mackerel)
  
  Degrees of Freedom: 278 total; 266.4857 Residual
  Residual Deviance: 359.4476 
  
  > print(gam(log(Density) ~ lo(log(mack.depth)) + lo(mack.lat, 
  +     mack.long), data = mackerel))
  Call:
  gam(formula = log(Density) ~ lo(log(mack.depth)) + lo(mack.lat, 
      mack.long), data = mackerel)
  
  Degrees of Freedom: 278 total; 266.0766 Residual
  Residual Deviance: 271.311 
  
  > print(gam(log(Density) ~ lo(log(mack.depth)) + lo(Temperature), 
  +     data = mackerel))
  Call:
  gam(formula = log(Density) ~ lo(log(mack.depth)) + lo(Temperature), 
      data = mackerel)
  
  Degrees of Freedom: 278 total; 270.9924 Residual
  Residual Deviance: 335.5316 
  
  > par(mfrow = c(2, 2))
  
  > plot.gam(model1, se = TRUE)
  Error in eval(expr, envir, enclos) : could not find function "plot.gam"
  Calls: source -> withVisible -> eval -> eval
  Execution halted
* checking PDF version of manual ... OK
* DONE
Status: 2 ERRORs, 2 NOTEs