possum                 package:DAAG                 R Documentation

_P_o_s_s_u_m _M_e_a_s_u_r_e_m_e_n_t_s

_D_e_s_c_r_i_p_t_i_o_n:

     The 'possum' data frame consists of nine morphometric measurements
     on each of 104 mountain brushtail possums, trapped at seven sites
     from Southern Victoria to central Queensland.

_U_s_a_g_e:

     possum

_F_o_r_m_a_t:

     This data frame contains the following columns:

     _c_a_s_e observation number

     _s_i_t_e one of seven locations where possums were trapped

     _P_o_p a factor which classifies the sites as 'Vic' Victoria, 'other'
          New South Wales or Queensland

     _s_e_x a factor with levels 'f' female, 'm' male 

     _a_g_e age

     _h_d_l_n_g_t_h head length

     _s_k_u_l_l_w skull width

     _t_o_t_l_n_g_t_h total length

     _t_a_i_l_l tail length

     _f_o_o_t_l_g_t_h foot length

     _e_a_r_c_o_n_c_h ear conch length

     _e_y_e distance from medial canthus to lateral canthus of right eye

     _c_h_e_s_t chest girth (in cm)

     _b_e_l_l_y belly girth (in cm)

_S_o_u_r_c_e:

     Lindenmayer, D. B., Viggers, K. L., Cunningham, R. B., and
     Donnelly, C. F. 1995. Morphological variation among columns of the
     mountain brushtail possum, Trichosurus caninus Ogilby
     (Phalangeridae: Marsupiala). Australian Journal of Zoology 43:
     449-458.

_E_x_a_m_p_l_e_s:

     boxplot(earconch~sex, data=possum)
     pause()

     sex <- as.integer(possum$sex)
     oldpar <- par(oma=c(2,4,5,4))
     pairs(possum[, c(9:11)], pch=c(0,2:7), col=c("red","blue"),
       labels=c("tail\nlength","foot\nlength","ear conch\nlength"))
     chh <- par()$cxy[2]; xleg <- 0.05; yleg <- 1.04
     oldpar <- par(xpd=TRUE)  
     legend(xleg, yleg, c("Cambarville", "Bellbird", "Whian Whian  ",
       "Byrangery", "Conondale  ","Allyn River", "Bulburin"), pch=c(0,2:7),
       x.intersp=1, y.intersp=0.75, cex=0.8, xjust=0, bty="n", ncol=4)
     text(x=0.2, y=yleg - 2.25*chh, "female", col="red", cex=0.8, bty="n")
     text(x=0.75, y=yleg - 2.25*chh, "male", col="blue", cex=0.8, bty="n")
     par(oldpar)
     pause()

     sapply(possum[,6:14], function(x)max(x,na.rm=TRUE)/min(x,na.rm=TRUE))
     pause()

     here <- na.omit(possum$footlgth)
     possum.prc <- princomp(possum[here, 6:14])
     pause()

     plot(possum.prc$scores[,1] ~ possum.prc$scores[,2],
       col=c("red","blue")[as.numeric(possum$sex[here])],
       pch=c(0,2:7)[possum$site[here]], xlab = "PC1", ylab = "PC2")
       # NB: We have abbreviated the axis titles
     chh <- par()$cxy[2]; xleg <- -15; yleg <- 20.5
     oldpar <- par(xpd=TRUE)
     legend(xleg, yleg, c("Cambarville", "Bellbird", "Whian Whian  ",
       "Byrangery", "Conondale  ","Allyn River", "Bulburin"), pch=c(0,2:7),
       x.intersp=1, y.intersp=0.75, cex=0.8, xjust=0, bty="n", ncol=4)
     text(x=-9, y=yleg - 2.25*chh, "female", col="red", cex=0.8, bty="n")
     summary(possum.prc, loadings=TRUE, digits=2)
     par(oldpar)
     pause()

     require(MASS)
     here <- !is.na(possum$footlgth)
     possum.lda <- lda(site ~ hdlngth+skullw+totlngth+ taill+footlgth+
       earconch+eye+chest+belly, data=possum, subset=here)
     options(digits=4)
     possum.lda$svd   # Examine the singular values   
     plot(possum.lda, dimen=3)
       # Scatterplot matrix - scores on 1st 3 canonical variates (Figure 11.4)
     possum.lda

