dr.pvalue {dr} | R Documentation |
Returns an approximate quantile for a weighted sum of independent \chi^2(1) random variables.
dr.pvalue(coef,f,chi2approx=c("bx","wood"),...) bentlerxie.pvalue(coef, f) wood.pvalue(coef, f, tol=0.0, print=FALSE)
coef |
a vector of nonnegative weights |
f |
Observed value of the statistic |
chi2approx |
Which approximation should be used? |
tol |
tolerance for Wood's method. |
print |
Printed output for Wood's method |
... |
Arguments passed from dr.pvalue to
wood.pvalue. |
For Bentler-Xie, we approximate f by c \chi^2(d) for values of c and d computed by the function. The Wood approximation is more complicated.
Returns a data.frame with four named components:
test |
The input argument f . |
test.adj |
For Bentler-Xie, returns cf; for Wood, returns NA . |
df.adj |
For Bentler-Xie, returns d; for Wood, returns NA . |
pval.adj |
Approximate p.value. |
Sanford Weisberg <sandy@stat.umn.edu>
Peter M. Bentler and Jun Xie (2000), Corrections to test statistics in principal Hessian directions. Statistics and Probability Letters, 47, 381-389.
Wood, Andrew T. A. (1989) An F approximation to the distribution of a linear combination of chi-squared variables. Communications in Statistics: Simulation and Computation, 18, 1439-1456.