| internals_for_distr {distr} | R Documentation |
These functions are used internally by package distr.
.is.vector.lattice(x)
.is.consistent(lattice, support, eq.space = TRUE)
.make.lattice.es.vector(x)
.inArgs(arg, fct)
.isEqual(p0, p1, tol = min( getdistrOption("TruncQuantile")/2,
.Machine$double.eps^.7))
.isEqual01(x)
.isIn(p0, pmat, tol = min( getdistrOption("TruncQuantile")/2,
.Machine$double.eps^.7
))
.setEqual(x, y, tol = 1e-7)
.presubs(inp, frompat, topat)
.makeD(object, argList, stand = NULL)
.makeP(object, argList, sign = TRUE, correct = NULL)
.makeQ(object, lastCall, sign = TRUE, Cont = TRUE)
.plusm(e1, e2, Dclass = "DiscreteDistribution")
.multm(e1, e2, Dclass = "DiscreteDistribution")
.notwithLArg(D)
.getObjName(i = 1)
.discretizeP(D, lower, upper, h)
.fm(x,f)
.fM(x,f)
.fM2(x,f)
.makeDd(x,y, yleft, yright)
.makePd(x,y, yleft, yright)
.makeQd(x,y, yleft, yright)
.makeQc(x,y, yleft, yright)
.makeDNew(x, dx, h = NULL, Cont = TRUE, standM = "sum")
.makePNew(x, dx, h = NULL, notwithLLarg = FALSE,
Cont = TRUE, myPf = NULL, pxl = NULL, pxu = NULL)
.makeQNew(x, px.l, px.u, notwithLLarg = FALSE, yL , yR, Cont = TRUE)
x |
a (numeric) vector |
y |
a (numeric) vector |
f |
a function in one (numeric) argument |
lattice |
a lattice (of class Lattice) |
support |
a support vector |
eq.space |
logical: shall we check for the support to be equally spaced? |
arg |
a formal argument as character |
fct |
a function |
p0,p1 |
(numeric) vectors |
pmat |
(matrix) a matrix with two columns where row-wise the left column is smaller than the right one |
tol |
an error tolerance (numeric) |
e1 |
a distribution object |
e2 |
a numeric |
object |
a distribution object |
argList |
an (unevaluated) list of arguments passed to m(object)
where m is in d,p,q |
stand |
factor for a (Lebesgue) density to integrate to 1 |
sign |
the sign of the second operand — for multiplication at the moment |
correct |
unevaluated R-code to correct for right-continuity (for multiplication with negative numerics at the moment) |
lastCall |
unevaluated R-Code —gives how the result of a call to
q(e1) is further transformed |
Cont |
logical: TRUE if object is continuous |
DClass |
character: name of distribution class |
D |
a distribution object |
i |
an integer |
yleft, yright |
extrapolation value beyond left/right endpoint of grid |
h |
numeric: grid width |
standM |
standardization method — summation or integration |
notwithLLarg |
logical — can we use log.p, lower.tail
arguments for p,q-methods of first operand? |
dx |
numeric: vector of cell-probabilities for the (discretized) distribution |
myPf |
function with args x,y, yleft, yright
(as approxfun):
if given: replaces approxfun as interpolation method for
continuos distributions |
pxl,pxu |
numeric: if given vector of (lower/upper) cumulative probabilities |
yL, yR |
argmin / argmax of p()-method |
inp |
either a language object or a character vector |
frompat |
vector of character strings containing regular expressions (or
character string for fixed = TRUE) to be matched in the
given character vector. Coerced by as.character to a
character string if possible; (as argument pattern in
gsub — but possibly of length >1). |
topat |
a (vector of) replacement(s) for matched pattern in
.presubs.
Coerced to character if possible. For fixed = FALSE this
can include backreferences "\1"' to "\9" to
parenthesized subexpressions of pattern. For
perl = TRUE only, it can
also contain "\U" or "\L" to convert the rest of the
replacement to upper or lower case; (as argument replacement
in gsub— but possibly of length >1). |
.is.vector.lattice checks whether a given vector x is equally
spaced.
.is.consistent checks whether a given support vector support is
consistent to a given lattice lattice — with or without checking
if support is equally spaced. .make.lattice.es.vector
makes an object of class Lattice out of a given (equally spaced) vector
x.
.inArgs checks whether an argument arg is a formal argument of
fct — not vectorized.
.isEqual checks whether p0 and p1 are equal to given
tolerance.
.isIn checks whether p0 lies in any of the intervals given by
matrix pmat to given tolerance.
.isEqual01(x) checks whether x is 0 or 1 to given tolerance.
.setEqual sets all elements of x which are equal to some element of y
up to tolerance tol, to exactly the respective element of y.
.notwithLArg checks whether object D was generated by simulations
or if its slots p,q do not have lower.tail arguments.
.getObjName returns the name of the object in the ith operand.
.discretizeP discretizes D to a grid of probabilities from
lower to upper with width h.
.fm, .fM return the smallest / biggest value in (0,1) such that
f(x) is finite; .fM2 is a variant of .fM using a
lower.tail = FALSE argument.
.makeD, .makeP, .makeQ generate slots p,d,q for
binary operations e1 /op/ e2 for a distribution object e1
and a numeric e2 —for the moment only /op/'s
+,-,*,/ are implemented.
.plusm, .multm more specifically use .makeD, .makeP,
.makeQ to generate slots p,d,q for +, *,
respectively.
.makeDd, .makePd, .makeQd provide discrete analogues to
approxfun for interpolation at non grid-values
.makeQc is an analogue to makeQd for absolutely continuous
distributions using approxfun.
.makeDNew generates slot d for a new distribution object.
In case of a discrete distribution it produces a step function with
stepfun (using .makeDd) and standardizes to 1 by summation.
In case of a continuous distribution it produces a density function with
approxfun and standardizes to 1 by integration if the latter fails,
it uses a trapezoid rule / summation for this purpose.
.makePNew generates slot p for a new distribution object.
In case of a discrete distribution it produces a step function from
cumsum applied to dx —or from pxl if this is given, with
stepfun (using .makePd).
In case of a continuous distribution it produces a cdf with
approxfun. In case of RtoDPQ, approxfun is replaced by
myPf which calls ecdf directly.
.makeQNew generates slot q for a new distribution object.
In case of a discrete distribution it produces a step function
(using .makeQd). Special care is taken for left continuity...
In case of a continuous distribution it produces a quantile function with
approxfun.
.is.vector.lattice |
logical (length 1) |
.is.consistent |
logical (length 1) |
.notwithLArg |
logical (length 1) |
.make.lattice.es.vector |
an object of class Lattice |
.inArgs |
logical (length 1) |
.isIn, .isEqual,.isEqual01 |
vector of logical |
.fm,.fM, .fM2 |
a numeric of length 1 |
.plusm,.multm |
an object of class DiscreteDistribution or
AbscontDistribution according to argument DClass |
.getObjName |
character |
.discretizeP |
numeric — the probabilities for the grid-values |
.makeDd,.makePd, .makeQd |
a function with args
x, y, yleft, yright |
.makeD,.makeDNew |
a function with args x, log = FALSE |
.makeP,.makePNew |
a function with args q, lower.tail = TRUE,
log.p = FALSE |
.makeQ,.makeQNew |
a function with args p, lower.tail = TRUE,
log.p = FALSE |
Peter Ruckdeschel Peter.Ruckdeschel@uni-bayreuth.de
LatticeDistribution,
RtoDPQ,
RtoDPQ.d,
convpow,
operators,
plot-methods