gof.sandwich {EDFtest} | R Documentation |
This function tests the hypothesis that data y come from
distribution Fdist
with unknown parameter values theta.
Estimates of theta must be provided in thetahat
.
gof.sandwich(y, x = NULL, Fdist, thetahat, Score, m = max(n, 100), ...)
y |
A random sample or the response of regression problem. |
x |
The matrix of covariates. |
Fdist |
User supplied function to compute probability integral transform of y. |
thetahat |
Parameter estimates by MLE. |
Score |
User supplied function to compute 3 components of the score function
an n by p matrix with entries partial log f(y_i, |
m |
Eigenvalues are extracted for an m by m grid of the covariance function. |
... |
Other inputs passed to |
It uses a large sample approximation to the limit distribution based on the use of the score function components to estimate the Fisher information and the limiting covariance function of the empirical process.
The estimates thetahat
should be roots of the likelihood equations.
Cramér-von Mises, Anderson-Darling and Watson statistics and their P-values.
gof
for generic functions using imhof
function;
gof.bootstrap
for generic functions using bootstrap method.
sample = rnorm(n=100,mean=0,sd=1)
mle = estimate.normal(sample)
cdf.normal.user = function(x,theta){
pnorm(x,mean=theta[1],sd=theta[2])
}
score.normal.user = function(x,theta){
sig=theta[2]
mu=theta[1]
s.mean= (x-mu)/sig
s.sd= s.mean^2/sig-length(x)/sig
cbind(s.mean/sig,s.sd)
}
output = gof.sandwich(y=sample,Fdist=cdf.normal.user,thetahat=mle,Score=score.normal.user,m=100)
output