FTres {kequate} | R Documentation |
Freeman-Tukey Residuals
Description
Calculates the Freeman-Tukey residuals for log-linear models of frequency data. If the frequencies are assumed to be Poisson distributed, then the Freeman-Tukey residuals are approximately normal distributed.
Usage
FTres(obs, fit)
Arguments
obs |
A numeric vector containing the observed frequencies. |
fit |
A numeric vector containing the estimated frequencies. |
Details
For an observed frequency n_{i}
and the estimated frequency m_{i}
, the Freeman-Tukey residual FT_{i}
is defined as
FT_{i} = \sqrt{n_{i}}+\sqrt{n_{i}+1}-\sqrt{4m_{i}+1}.
Value
A numeric vector containing the Freeman-Tukey residuals.
Author(s)
bjorn.andersson@statistik.uu.se
kenny.branberg@stat.umu.se
marie.wiberg@stat.umu.se
References
Andersson, B., Branberg, K., and Wiberg, M. (2013). Performing the Kernel Method of Test Equating with the Package kequate. Journal of Statistical Software, 55(6), 1–25. <doi:10.18637/jss.v055.i06>
Holland, P.W, Thayer, D. (1998). Univariate and Bivariate Loglinear Models for Discrete Test Score Distributions ETS Technical Report No 98-1.
See Also
Examples
#Example data:
P<-c(5, 20, 35, 25, 15)
x<-0:4
glmx<-glm(P~I(x)+I(x^2), family="poisson", x=TRUE)
res<-FTres(glmx$y, glmx$fitted.values)