Keywords - Function groups - @ A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

 Quantlet: plothare Description: plots a hare density, distribution function, hazard function or survival function for a model estimated by harefit.

 Usage: plothare(fit{,cov,what,n,which,time,xlim,type}) Input: fit a list like the output from harefit. cov a (1 x fit.ncov) matrix, indicating for which combination of covariates the plot should be made (fit.ncov is the number of covariates used during fitting the model). Can be omitted only if fit.ncov is 0. what an optional string containing one or more letters separated by commas specifying what should be plotted (default is "d"): d (density), p (distribution function), s (survival function) or h (hazard function). n an optional number of equally spaced points at which to plot the fit (default is 100). which an optional number (default is 0) setting for which coordinate the plot should be made. 0: time; positive value i: covariate i. Note that if which is the positive value i, then the element corresponding to this covariate must be given in cov even though its actual value is irrelevant. time a time vector; if which is not equal to 0, the value of time for which the plot should be made. Otherwise, it can be omitted. xlim an optional 2 x 1 vector containing lower and upper bounds for x-axis. type an optional one-character string indicating what type of plot should be drawn. Possible types are "p" for points, and "l" for lines (default).

Note:
This quantlet uses "plot" to create graphics, thus display variable "plotdisplay" is created and can be used for further modification of the plot.

Example:
```library("hazreg")
randomize(111)
n = 500
p = 2
beta = 1|2                      ; regression parameter
z = 1 + uniform(n,p)            ; covariates
y = -log(1-uniform(n))          ; exponential survival
y = y./exp(z*beta)              ; covariate effects
c = 4*uniform(n)                ; uniform censoring
t = min(y~c,2)                  ; censored time
delta =(y<=c)                  ; censoring indicator
fit=harefit(t,delta,z)
haresummary(fit)
plothare(fit,1.1~1.4,"p,s")

```
Result:
```Along with the summary, the estimated distribution and
survival functions are plotted.

Contents of sum

[ 1,] "dim A/D   loglik      AIC         penalty  "
[ 2,] "                                min     max"
[ 3,] "  0 Add  -1.6e-46 -9.2e+102 1.4e+02 1.4e+02"
[ 4,] "  0 Add  5.6e+175 -5.9e-144      42      42"
[ 5,] "  0 Add   9.7e+43 -6.2e-127     1.3     1.3"
[ 6,] "  0 Add -7.3e-252  2.7e-273    0.00"
[ 7,] "                                              "
[ 8,] "the present optimal number of dimensions is 3."
[ 9,] "penalty(AIC) was the default: BIC=log(samplesize): log(500)=6.2"
[10,] "                                                         "
[11,] "  dim1           dim2            beta       SE       Wald"
[12,] "Constant                           0.21      0.32    0.64"
[13,] "Co-2  linear                        1.8      0.16      11"
[14,] "Co-1  linear                          1      0.16     6.5"
```

Author: P. Cizek, W. Haerdle, 20010508 license MD*Tech
(C) MD*TECH Method and Data Technologies, 05.02.2006