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.Rapp.history
executable file
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.Rapp.history
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?wald.test
library(aod)
?wald.test
data(orob2)#
fm <- quasibin(cbind(y, n - y) ~ seed * root, data = orob2)#
# Wald test for the effect of root
str(fm)
wald.test(b = coef(fm), Sigma = vcov(fm), Terms = 3:4)
coef(fm)
vcov(fm)
names(fm)
args(vcov)
?predict
rnorm(1000) -> x
rnorm(1000000) -> x
ys <- sapply(1:10, function(i) sample(0:1, replace=TRUE))
dim(ys)
ys <- sapply(1:10, function(i) sample(0:1, 10^6, replace=TRUE))
dim(ys)
ys <- lapply(1:10, function(i) ys[, i])
str(ys)
head(x)
system.time(model <- glm(ys[[1]]~x))
system.time(model <- glm(ys[[1]][1:50000]~x, family='binomial'))
system.time(model <- glm(ys[[1]][1:50000]~x[1:50000], family='binomial'))
system.time(model <- glm(ys[[1]][1:100000]~x[1:100000], family='binomial'))
parallel::mclapply(ys, function(y) glm(y[1:100000]~x[1:100000], family='binomial'))
system.time(parallel::mclapply(ys, function(y) glm(y[1:100000]~x[1:100000], family='binomial')->model))
system.time(parallel::mclapply(ys, function(y) glm(y[1:100000]~x[1:100000], family='binomial'))->model)
system.time(parallel::mclapply(ys, function(y) glm(y[1:100000]~x[1:100000], family='binomial'), mc.core=4)->model)
system.time(parallel::mclapply(ys, function(y) glm(y[1:100000]~x[1:100000], family='binomial'), mc.core=2)->model)
args(parallel::mclapply)
system.time(parallel::mclapply(ys, function(y) {glm(y[1:100000]~x[1:100000], family='binomial')}, mc.cores=2)->model)
system.time(parallel::mclapply(ys, function(y) {glm(y[1:100000]~x[1:100000], family='binomial')}, mc.cores=2)->model)
system.time(parallel::mclapply(ys, function(y) {glm(y[1:100000]~x[1:100000], family='binomial')}, mc.cores=2)->model)
system.time(parallel::mclapply(ys, function(y) {glm(y[1:100000]~x[1:100000], family='binomial')}, mc.cores=2)->model)
system.time(parallel::mclapply(ys, function(y) {glm(y[1:100000]~x[1:100000], family='binomial')}, mc.cores=2)->model)
system.time(parallel::mclapply(ys, function(y) {glm(y[1:100000]~x[1:100000], family='binomial')}, mc.cores=2)->model)
system.time(parallel::mclapply(ys, function(y) {glm(y[1:100000]~x[1:100000], family='binomial')}, mc.cores=2)->model)
system.time(parallel::mclapply(ys, function(y) {glm(y[1:100000]~x[1:100000], family='binomial')}, mc.cores=4)->model)
system.time(parallel::mclapply(ys, function(y) {glm(y[1:100000]~x[1:100000], family='binomial')}, mc.cores=8)->model)
system.time(parallel::mclapply(ys, function(y) {glm(y[1:100000]~x[1:100000], family='binomial')}, mc.cores=10)->model)
x <- matrix(x, nc=10)
dim(x)
system.time(parallel::mclapply(ys, function(y) {glm(y[1:100000]~x[, 1:3], family='binomial')}, mc.cores=10)->model)
system.time(parallel::mclapply(ys, function(y) {glm(y[1:100000]~x[, 1:3], family='binomial')}, mc.cores=5)->model)
?system.time
ys <- lapply(1:100, function(i) sample(0:1, 100000, replace=TRUE))
str(ys)
system.time(parallel::mclapply(ys, function(y) {glm(y~x[, 1:3], family='binomial')}, mc.cores=10)->model)
system.time(parallel::mclapply(ys, function(y) {glm(y~x[, 1:3], family='binomial')}, mc.cores=5)->model)
system.time(parallel::mclapply(ys, function(y) {glm(y~x[, 1:3], family='binomial')}, mc.cores=20)->model)