Mixing
list() is not updating in the for loop in R
0
I want to estimate the parameters of the skew normal distribution using mle2 function in r. I have copied my r function below.
library(bbmle)
library(sn)
y = c(rsn(n=50, xi=0, omega=1, alpha=1, tau=0, dp=NULL), rsn(n=50, xi=0, omega=1, alpha=6, tau=0, dp=NULL))
n= length(y)
sn.fit = function(xi, omega, alpha){
-sum(dsn(y, xi=0, omega=1, alpha, log = TRUE))
}
parl = list()
for(i in 1:(n-1)){
dat = list(y[1:i])
parl[[i]]= mle2(sn.fit, start = list(xi = 0, omega = 1, alpha = 1), data = dat)@coef
}
parll = do.call("rbind", parl)
parll
The output is given below.
> parll
xi omega alpha
[1,] 0 1 1.408533
[2,] 0 1 1.408533
[3,] 0 1 1.408533
[4,] 0 1 1.408533
[5,] 0 1 1.408533
[6,] 0 1 1.408533
[7,] 0 1 1.408533
[8,] 0 1 1.408533
[9,] 0 1 1.408533
[10,] 0 1 1.408533
[11,] 0 1 1.408533
[12,] 0 1 1.408533
Since my intention is to estimate alpha for y[1:i] for i=1,...,(n-1). Why my result is not updating into the list?
Thank you in advance.
r list for-loop mle
asked Nov 19 '18 at 19:32
score324score324
999
add a comment |
0
I want to estimate the parameters of the skew normal distribution using mle2 function in r. I have copied my r function below.
library(bbmle)
library(sn)
y = c(rsn(n=50, xi=0, omega=1, alpha=1, tau=0, dp=NULL), rsn(n=50, xi=0, omega=1, alpha=6, tau=0, dp=NULL))
n= length(y)
sn.fit = function(xi, omega, alpha){
-sum(dsn(y, xi=0, omega=1, alpha, log = TRUE))
}
parl = list()
for(i in 1:(n-1)){
dat = list(y[1:i])
parl[[i]]= mle2(sn.fit, start = list(xi = 0, omega = 1, alpha = 1), data = dat)@coef
}
parll = do.call("rbind", parl)
parll
The output is given below.
> parll
xi omega alpha
[1,] 0 1 1.408533
[2,] 0 1 1.408533
[3,] 0 1 1.408533
[4,] 0 1 1.408533
[5,] 0 1 1.408533
[6,] 0 1 1.408533
[7,] 0 1 1.408533
[8,] 0 1 1.408533
[9,] 0 1 1.408533
[10,] 0 1 1.408533
[11,] 0 1 1.408533
[12,] 0 1 1.408533
Since my intention is to estimate alpha for y[1:i] for i=1,...,(n-1). Why my result is not updating into the list?
Thank you in advance.
r list for-loop mle
asked Nov 19 '18 at 19:32
score324score324
999
1
You've hard codedyinto thesn.fitfunction. Thus you are using the same data for every call, it's not changing. Thedata=part only works if you pass a formula, not a function tomle2.
– MrFlick
Nov 19 '18 at 19:50
@MrFlick, Am I able to improve this? Thanks.
– score324
Nov 19 '18 at 19:59
@MrFlick is this correct? right?parl = list() for(i in 1:(n-1)){ dat = y[1:i] sn.fit = function(xi, omega, alpha){ -sum(dsn(dat, xi=0, omega=1, alpha, log = TRUE)) } parl[[i]]= mle2(sn.fit, start = list(xi = 0, omega = 1, alpha = 1), data = list(dat))@coef } parll = do.call("rbind", parl) parll
– score324
Nov 19 '18 at 20:01
add a comment |
0
0
0
I want to estimate the parameters of the skew normal distribution using mle2 function in r. I have copied my r function below.
library(bbmle)
library(sn)
y = c(rsn(n=50, xi=0, omega=1, alpha=1, tau=0, dp=NULL), rsn(n=50, xi=0, omega=1, alpha=6, tau=0, dp=NULL))
n= length(y)
sn.fit = function(xi, omega, alpha){
-sum(dsn(y, xi=0, omega=1, alpha, log = TRUE))
}
parl = list()
for(i in 1:(n-1)){
dat = list(y[1:i])
parl[[i]]= mle2(sn.fit, start = list(xi = 0, omega = 1, alpha = 1), data = dat)@coef
}
parll = do.call("rbind", parl)
parll
The output is given below.
> parll
xi omega alpha
[1,] 0 1 1.408533
[2,] 0 1 1.408533
[3,] 0 1 1.408533
[4,] 0 1 1.408533
[5,] 0 1 1.408533
[6,] 0 1 1.408533
[7,] 0 1 1.408533
[8,] 0 1 1.408533
[9,] 0 1 1.408533
[10,] 0 1 1.408533
[11,] 0 1 1.408533
[12,] 0 1 1.408533
Since my intention is to estimate alpha for y[1:i] for i=1,...,(n-1). Why my result is not updating into the list?
Thank you in advance.
r list for-loop mle
asked Nov 19 '18 at 19:32
score324score324
999
I want to estimate the parameters of the skew normal distribution using mle2 function in r. I have copied my r function below.
library(bbmle)
library(sn)
y = c(rsn(n=50, xi=0, omega=1, alpha=1, tau=0, dp=NULL), rsn(n=50, xi=0, omega=1, alpha=6, tau=0, dp=NULL))
n= length(y)
sn.fit = function(xi, omega, alpha){
-sum(dsn(y, xi=0, omega=1, alpha, log = TRUE))
}
parl = list()
for(i in 1:(n-1)){
dat = list(y[1:i])
parl[[i]]= mle2(sn.fit, start = list(xi = 0, omega = 1, alpha = 1), data = dat)@coef
}
parll = do.call("rbind", parl)
parll
The output is given below.
> parll
xi omega alpha
[1,] 0 1 1.408533
[2,] 0 1 1.408533
[3,] 0 1 1.408533
[4,] 0 1 1.408533
[5,] 0 1 1.408533
[6,] 0 1 1.408533
[7,] 0 1 1.408533
[8,] 0 1 1.408533
[9,] 0 1 1.408533
[10,] 0 1 1.408533
[11,] 0 1 1.408533
[12,] 0 1 1.408533
Since my intention is to estimate alpha for y[1:i] for i=1,...,(n-1). Why my result is not updating into the list?
Thank you in advance.
r list for-loop mle
r list for-loop mle
asked Nov 19 '18 at 19:32
score324score324
999
asked Nov 19 '18 at 19:32
score324score324
999
asked Nov 19 '18 at 19:32
score324score324
999
asked Nov 19 '18 at 19:32
score324score324
999
asked Nov 19 '18 at 19:32
score324score324
999
999
1
You've hard codedyinto thesn.fitfunction. Thus you are using the same data for every call, it's not changing. Thedata=part only works if you pass a formula, not a function tomle2.
– MrFlick
Nov 19 '18 at 19:50
@MrFlick, Am I able to improve this? Thanks.
– score324
Nov 19 '18 at 19:59
@MrFlick is this correct? right?parl = list() for(i in 1:(n-1)){ dat = y[1:i] sn.fit = function(xi, omega, alpha){ -sum(dsn(dat, xi=0, omega=1, alpha, log = TRUE)) } parl[[i]]= mle2(sn.fit, start = list(xi = 0, omega = 1, alpha = 1), data = list(dat))@coef } parll = do.call("rbind", parl) parll
– score324
Nov 19 '18 at 20:01
add a comment |
1
You've hard codedyinto thesn.fitfunction. Thus you are using the same data for every call, it's not changing. Thedata=part only works if you pass a formula, not a function tomle2.
– MrFlick
Nov 19 '18 at 19:50
@MrFlick, Am I able to improve this? Thanks.
– score324
Nov 19 '18 at 19:59
@MrFlick is this correct? right?parl = list() for(i in 1:(n-1)){ dat = y[1:i] sn.fit = function(xi, omega, alpha){ -sum(dsn(dat, xi=0, omega=1, alpha, log = TRUE)) } parl[[i]]= mle2(sn.fit, start = list(xi = 0, omega = 1, alpha = 1), data = list(dat))@coef } parll = do.call("rbind", parl) parll
– score324
Nov 19 '18 at 20:01
1
1
You've hard coded
y into the sn.fit function. Thus you are using the same data for every call, it's not changing. The data= part only works if you pass a formula, not a function to mle2.– MrFlick
Nov 19 '18 at 19:50
You've hard coded
y into the sn.fit function. Thus you are using the same data for every call, it's not changing. The data= part only works if you pass a formula, not a function to mle2.– MrFlick
Nov 19 '18 at 19:50
@MrFlick, Am I able to improve this? Thanks.
– score324
Nov 19 '18 at 19:59
@MrFlick, Am I able to improve this? Thanks.
– score324
Nov 19 '18 at 19:59
@MrFlick is this correct? right?
parl = list() for(i in 1:(n-1)){ dat = y[1:i] sn.fit = function(xi, omega, alpha){ -sum(dsn(dat, xi=0, omega=1, alpha, log = TRUE)) } parl[[i]]= mle2(sn.fit, start = list(xi = 0, omega = 1, alpha = 1), data = list(dat))@coef } parll = do.call("rbind", parl) parll– score324
Nov 19 '18 at 20:01
@MrFlick is this correct? right?
parl = list() for(i in 1:(n-1)){ dat = y[1:i] sn.fit = function(xi, omega, alpha){ -sum(dsn(dat, xi=0, omega=1, alpha, log = TRUE)) } parl[[i]]= mle2(sn.fit, start = list(xi = 0, omega = 1, alpha = 1), data = list(dat))@coef } parll = do.call("rbind", parl) parll– score324
Nov 19 '18 at 20:01
add a comment |
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1
You've hard coded
yinto thesn.fitfunction. Thus you are using the same data for every call, it's not changing. Thedata=part only works if you pass a formula, not a function tomle2.– MrFlick
Nov 19 '18 at 19:50
@MrFlick, Am I able to improve this? Thanks.
– score324
Nov 19 '18 at 19:59
@MrFlick is this correct? right?
parl = list() for(i in 1:(n-1)){ dat = y[1:i] sn.fit = function(xi, omega, alpha){ -sum(dsn(dat, xi=0, omega=1, alpha, log = TRUE)) } parl[[i]]= mle2(sn.fit, start = list(xi = 0, omega = 1, alpha = 1), data = list(dat))@coef } parll = do.call("rbind", parl) parll– score324
Nov 19 '18 at 20:01