Calculating Log-likelihood for the Skew Normal Distribution in R
1
library(sn)
library(fGarch)
library(maxLik)
set.seed(12)
nl = 100
locl = 0
scalel = 1
shapel = 1
#data
y = c(rsn(n=nl, xi=locl, omega=scalel, alpha=shapel, tau=0, dp=NULL))
Assume only the shape parameter is unknown.
snormFit <- function(x, ...)
start = c(mean = 0, sd = 1, xi = 1)
# Log-likelihood Function:
loglik = function(x, y = x)
f = -sum(log(dsnorm(y, 0, 1, x[3])))
f
# Minimization:
fit = nlminb(start = start, objective = loglik, lower = c(-Inf, 0, 0),
upper = c( Inf, Inf, Inf), y = x)
# Return Value:
fit
shape.l = snormFit(y)$par
Warning message:
In nlminb(start = start, objective = loglik, lower = c(-Inf, 0, :
NA/NaN function evaluation
> shape.l
mean sd xi
0.0000000 1.0000000 0.8216856
# Likelihood
logLik.sn = sum(log(dnorm(shape.l*y)))
Warning message:
In shape.l * y :
longer object length is not a multiple of shorter object length
logLik.sn
[1] -112.9638
IS the way I computed the log-likelihood correct? However, I am getting some warning messages. What is the reason for this? Are there any other ways to compute the log-likelihood for skew normal distribution in R?
Thank you in advance.
r normal-distribution skew log-likelihood
asked Nov 12 '18 at 19:51
score324
999
add a comment |
1
library(sn)
library(fGarch)
library(maxLik)
set.seed(12)
nl = 100
locl = 0
scalel = 1
shapel = 1
#data
y = c(rsn(n=nl, xi=locl, omega=scalel, alpha=shapel, tau=0, dp=NULL))
Assume only the shape parameter is unknown.
snormFit <- function(x, ...)
start = c(mean = 0, sd = 1, xi = 1)
# Log-likelihood Function:
loglik = function(x, y = x)
f = -sum(log(dsnorm(y, 0, 1, x[3])))
f
# Minimization:
fit = nlminb(start = start, objective = loglik, lower = c(-Inf, 0, 0),
upper = c( Inf, Inf, Inf), y = x)
# Return Value:
fit
shape.l = snormFit(y)$par
Warning message:
In nlminb(start = start, objective = loglik, lower = c(-Inf, 0, :
NA/NaN function evaluation
> shape.l
mean sd xi
0.0000000 1.0000000 0.8216856
# Likelihood
logLik.sn = sum(log(dnorm(shape.l*y)))
Warning message:
In shape.l * y :
longer object length is not a multiple of shorter object length
logLik.sn
[1] -112.9638
IS the way I computed the log-likelihood correct? However, I am getting some warning messages. What is the reason for this? Are there any other ways to compute the log-likelihood for skew normal distribution in R?
Thank you in advance.
r normal-distribution skew log-likelihood
asked Nov 12 '18 at 19:51
score324
999
add a comment |
1
1
1
library(sn)
library(fGarch)
library(maxLik)
set.seed(12)
nl = 100
locl = 0
scalel = 1
shapel = 1
#data
y = c(rsn(n=nl, xi=locl, omega=scalel, alpha=shapel, tau=0, dp=NULL))
Assume only the shape parameter is unknown.
snormFit <- function(x, ...)
start = c(mean = 0, sd = 1, xi = 1)
# Log-likelihood Function:
loglik = function(x, y = x)
f = -sum(log(dsnorm(y, 0, 1, x[3])))
f
# Minimization:
fit = nlminb(start = start, objective = loglik, lower = c(-Inf, 0, 0),
upper = c( Inf, Inf, Inf), y = x)
# Return Value:
fit
shape.l = snormFit(y)$par
Warning message:
In nlminb(start = start, objective = loglik, lower = c(-Inf, 0, :
NA/NaN function evaluation
> shape.l
mean sd xi
0.0000000 1.0000000 0.8216856
# Likelihood
logLik.sn = sum(log(dnorm(shape.l*y)))
Warning message:
In shape.l * y :
longer object length is not a multiple of shorter object length
logLik.sn
[1] -112.9638
IS the way I computed the log-likelihood correct? However, I am getting some warning messages. What is the reason for this? Are there any other ways to compute the log-likelihood for skew normal distribution in R?
Thank you in advance.
r normal-distribution skew log-likelihood
asked Nov 12 '18 at 19:51
score324
999
library(sn)
library(fGarch)
library(maxLik)
set.seed(12)
nl = 100
locl = 0
scalel = 1
shapel = 1
#data
y = c(rsn(n=nl, xi=locl, omega=scalel, alpha=shapel, tau=0, dp=NULL))
Assume only the shape parameter is unknown.
snormFit <- function(x, ...)
start = c(mean = 0, sd = 1, xi = 1)
# Log-likelihood Function:
loglik = function(x, y = x)
f = -sum(log(dsnorm(y, 0, 1, x[3])))
f
# Minimization:
fit = nlminb(start = start, objective = loglik, lower = c(-Inf, 0, 0),
upper = c( Inf, Inf, Inf), y = x)
# Return Value:
fit
shape.l = snormFit(y)$par
Warning message:
In nlminb(start = start, objective = loglik, lower = c(-Inf, 0, :
NA/NaN function evaluation
> shape.l
mean sd xi
0.0000000 1.0000000 0.8216856
# Likelihood
logLik.sn = sum(log(dnorm(shape.l*y)))
Warning message:
In shape.l * y :
longer object length is not a multiple of shorter object length
logLik.sn
[1] -112.9638
IS the way I computed the log-likelihood correct? However, I am getting some warning messages. What is the reason for this? Are there any other ways to compute the log-likelihood for skew normal distribution in R?
Thank you in advance.
r normal-distribution skew log-likelihood
r normal-distribution skew log-likelihood
asked Nov 12 '18 at 19:51
score324
999
asked Nov 12 '18 at 19:51
score324
999
asked Nov 12 '18 at 19:51
score324
999
asked Nov 12 '18 at 19:51
score324
999
asked Nov 12 '18 at 19:51
score324
999
999
add a comment |
add a comment |
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