3
set.seed(0); u <- runif(100)
7
y <- matrix(rnbinom(2*4,mu=4,size=1.5),2,4)
8
lib.size <- rep(50000,4)
10
fitNBP(y,group=group,lib.size=lib.size)
15
glmgam.fit(c(1,1),c(0,4))
16
glmgam.fit(X=cbind(1,c(1,0.5,0.5,0,0)),y=rchisq(5,df=1))
19
y <- rnbinom(5,mu=10,size=10)
20
glmnb.fit(X=cbind(1,c(1,0.5,0.5,0,0)),y=y,dispersion=0.1)
21
glmnb.fit(X=cbind(1,c(1,0.5,0.5,0,0)),y=y,dispersion=runif(6))
22
glmnb.fit(X=cbind(1,c(1,1,0,0,0)),y=c(0,0,6,2,9),dispersion=0.1)
29
m <- mixedModel2(y~x,random=z)
30
m$reml.residuals <- m$qr <- NULL
35
y <- c(-1,1,-2,2,0.5,1.7,-0.1)
37
Z <- model.matrix(~0+factor(c(1,1,2,2,3,3,4)))
38
m <- mixedModel2Fit(y,X,Z)
39
m$reml.residuals <- m$qr <- NULL
48
qresiduals(fit,dispersion=1)
51
fit <- glm(Days~Age,family=negative.binomial(2),data=quine)
52
print(summary(qresiduals(fit)))
53
fit <- glm.nb(Days~Age,link=log,data = quine)
54
print(summary(qresiduals(fit)))
60
g <- gauss.quad(5,"legendre")
61
zapsmall(data.frame(g),digits=15)
62
g <- gauss.quad(5,"chebyshev1")
63
zapsmall(data.frame(g),digits=15)
64
g <- gauss.quad(5,"chebyshev2")
65
zapsmall(data.frame(g),digits=15)
66
g <- gauss.quad(5,"hermite")
67
zapsmall(data.frame(g),digits=15)
68
g <- gauss.quad(5,"laguerre",alpha=5)
69
zapsmall(data.frame(g),digits=15)
70
g <- gauss.quad(5,"jacobi",alpha=5,beta=1.1)
71
zapsmall(data.frame(g),digits=15)
72
g <- gauss.quad.prob(5,dist="uniform")
73
zapsmall(data.frame(g),digits=15)
74
g <- gauss.quad.prob(5,dist="normal")
75
zapsmall(data.frame(g),digits=15)
76
g <- gauss.quad.prob(5,dist="beta")
77
zapsmall(data.frame(g),digits=15)
78
g <- gauss.quad.prob(5,dist="gamma")
79
zapsmall(data.frame(g),digits=15)
81
### extra tests done only locally
83
#GKSTest <- Sys.getenv("GKSTest")