I want to estimate the parameters of beta-normal distribution.I've used the maxLik package in r:
library(VGAM)
library(maxLik)
alfa=2;beta=3;mu=0;sigma=1
n=100
x=rbetanorm(n,alfa,beta,mu,sigma)
logLikFun=function(w){
alfa=w[1]
beta=w[2]
mu=w[3]
sigma=w[4]
ll={-n*log(beta(alfa,beta))+(alfa-1)*sum(log(pnorm((x-mu)/sigma,mean=0,sd=1)))+(beta-1)*sum(log(1-pnorm((x-mu)/sigma,mean=0,sd=1)))-n*log(sigma)+sum(log(dnorm((x-mu)/sigma,mean=0,sd=1)))}
ll
}
mle=maxLik(logLikFun,start=c(alfa=3,beta=2,mu=1,sigma=2))
summary(mle)
i want to estimate the parameters of beta-normal distribution.I've used the maxLik package
library(VGAM)
library(maxLik)
alfa=2;beta=3;mu=0;sigma=1
n=100
x=rbetanorm(n,alfa,beta,mu,sigma)
logLikFun=function(w){
alfa=w[1]
beta=w[2]
mu=w[3]
sigma=w[4]
ll={-n*log(beta(alfa,beta))+(alfa-1)*sum(log(pnorm((x-mu)/sigma,mean=0,sd=1)))+(beta-1)*sum(log(1-pnorm((x-mu)/sigma,mean=0,sd=1)))-n*log(sigma)+sum(log(dnorm((x-mu)/sigma,mean=0,sd=1)))}
ll
}
mle=maxLik(logLikFun,start=c(alfa=3,beta=2,mu=1,sigma=2))
summary(mle)
but it gives error:
----------------------------------
Maximum Likelihood estimation
Newton-Raphson maximisation, 4 iterations
Return code 2: successive function values within tolerance limit
Log-Likelihood: -86.16515
4 free parameters
Estimates:
Estimate Std. error t value Pr(> t)
alfa 3.000 Inf 0 1
beta 2.941 Inf 0 1
mu 1.000 Inf 0 1
sigma 2.000 Inf 0 1
--------------------------------------------
the problem is the infinite value for the errors which is not acceptable. I would be pleased if someone could solve this problem.
Hi I am a very experienced statistician and academic writer. I have completed several PhD level thesis projects involving advanced statistical analysis of data. I have worked with data from several companies and have done projects involving high level quantitative analysis and data interpretation skills to study the trends, time behaviour and compare the variables in the data. I can do advanced level analysis in SPSS, R, WEKA, TABLEAU and excel tools like machine learning, hypothesis testing, forecasting, T-test, ANOVA etc.
Looking forward to discussion,
Best Regards,
Suyash
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Relevant Skills and Experience
Matlab and Mathematica, R Programming Language, Software Development, Statistical Analysis, Statistics
Proposed Milestones
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