Nothing
#[export]
colhalfnorm.mle <- function(x) {
n <- dim(x)[1]
s <- sqrt( Rfast::colsums(x^2)/n )
loglik <- n/2 * log( 2 / pi / s) - n/2
res <- cbind(s, loglik)
colnames(res) <- c("sigma.squared", "loglik")
res
}
#[export]
colordinal.mle <- function (x, link = "logit") {
ina <- Rfast::colTabulate(x)
d <- dim(ina)[2]
for (i in 1:d) ina[, i] <- as.numeric(ina[, i])
k <- dim(ina)[1] - Rfast::colCountValues(ina, rep(0, d) )
ni <- Rfast::colCumSums(ina)/dim(x)[1]
if (link == "logit") {
param <- log(ni/(1 - ni))
} else param <- qnorm(ni)
ep <- which( is.infinite(param) )
param[ep] <- NA
loglik <- Rfast::rowsums( t(ina) * log( cbind( ni[1, ], Rfast::coldiffs( t(ni)) ) ), na.rm = TRUE )
list(param = param, loglik = loglik)
}
#[export]
collognorm.mle <- function(x) {
n <- dim(x)[1]
x <- Rfast::Log(x)
sx <- Rfast::colsums(x)
m <- sx/n
s <- Rfast::colsums(x^2)/n - m^2
loglik <- -0.5 * n * (log(2 * pi * s) + 1) - sx
res <- cbind(m, s, loglik)
colnames(res) <- c("mean", "variance", "loglik")
res
}
#[export]
collogitnorm.mle <- function(x) {
n <- dim(x)[1]
lx1 <- Rfast::Log(x)
lx2 <- Rfast::Log(1 - x)
y <- lx1 - lx2
sy <- Rfast::colsums(y)
m <- sy/n
s <- ( Rfast::colsums(y^2) - n * m^2 ) / n
loglik <- Rfast::rowsums( dnorm(t(y), m, sqrt(s), log = TRUE) ) - Rfast::colsums(lx1) - Rfast::colsums(lx2)
res <- cbind(m, n * s/(n - 1), loglik)
colnames(res) <- c("mean", "unbiased variance", "loglik")
res
}
#[export]
colborel.mle <- function(x) {
n <- dim(x)[1]
sx <- Rfast::colsums(x)
m <- 1 - n/sx
loglik <- -sx + n + Rfast::colsums( (x - 1) * log( t( t(x) * m ) ) ) -
Rfast::colsums( Rfast::Lgamma(x + 1) )
res <- cbind(m, loglik)
colnames(res) <- c("m", "loglik")
res
}
#[export]
colspml.mle <- function(x, tol = 1e-07, maxiters = 100, parallel = FALSE) {
res <- .Call( Rfast2_colspml_mle,x, tol, maxiters, parallel)
colnames(res) <- c("mu1", "mu2", "gamma", "loglik")
res
}
#[export]
colcauchy.mle <- function (x, tol = 1e-07, maxiters = 100, parallel = FALSE) {
res <- .Call(Rfast2_colcauchy_mle, x, tol, parallel, maxiters)
colnames(res) <- c("loglik", "location", "scale")
res
}
#[export]
colbeta.mle <- function(x, tol = 1e-07, maxiters = 100, parallel = FALSE) {
res <- .Call(Rfast2_colbeta_mle, x, tol, parallel, maxiters)
colnames(res) <- c("alpha", "beta", "loglik")
res
}
#[export]
colunitweibull.mle <- function(x, tol = 1e-07, maxiters = 100, parallel = FALSE) {
lx <- - log(x)
mod <- Rfast::colweibull.mle( lx, tol = tol, maxiters = maxiters, parallel = parallel )
param <- mod[, 1:2]
colnames(param) <- c("alpha", "beta")
a <- param[, 1] ; b <- param[, 2]
n <- dim(x)[1]
loglik <- Rfast::colsums(lx) + n * log(a * b) + (b - 1) * Rfast::colsums( log(lx) ) - a * Rfast::rowsums( t(lx)^b )
param <- cbind(param, loglik)
param
}
#[export]
colpowerlaw.mle <- function(x) {
n <- dim(x)[1]
x1 <- Rfast::colMins(x, TRUE)
com <- Rfast::colsums( log(x) ) - n * log(x1)
a <- 1 + n/com
loglik <- n * log((a - 1)/x1) - a * com
res <- cbind(a, loglik)
colnames(res) <- c("alpha", "loglik")
res
}
#[export]
colsp.mle <- function(x) {
n <- dim(x)[1]
slx <- Rfast::colsums( log(x) )
b <- - n / slx
loglik <- n * log(b) + (b - 1) * slx
res <- cbind(b, loglik)
colnames(res) <- c("beta", "loglik")
res
}
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