[R] "Help On optim"

PIKAL Petr petr.pikal at precheza.cz
Thu Aug 10 15:44:46 CEST 2017


Hi

I cannot help you with optim as it is beyond my expertise, but here are some notes.

Your mail is partially scrammbled due to HTML formating, please use plain text.
You say that you do not get right results, how they differ from your expectation?
Preferably provide some toy data as illustration.

Cheers
Petr

> -----Original Message-----
> From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of niharika
> singhal
> Sent: Thursday, August 10, 2017 11:54 AM
> To: r-help at r-project.org
> Subject: [R] "Help On optim"
>
> Hello,
>
>
>
> I have some parameters from Mclust function. The parameters are in the form
>
>
>
> *parametersDf *
>
>
>
> *      mu_1           mu_2          var_mc1    var_mc2        c1
>               c2    *
>
> *2   1.357283   2.962736       0.466154    0.1320129      0.5258975
>  0.4741025  *
>
> *21  8.357283   9.962736      0.466154    0.1320129      0.5258975
>  0.4741025  *
>
>
>
> Each row in the above data frame represent the segment and each segment
> contain two-mixture component. (Latter I will increase the segment and the
> mixture component)
>
>
>
> So for every segment with n mixture component I have to find the
>
>
>
> *max f(x) with –infinity < x < infinity*
>
>
>
> *f(x)=sum_i c_i N(O,mu_i,sigma_i).  *
>
>
>
> *Since i need to calculate the derivate f’ and set f’(x)=0  I thought of using
> Newton method *
>
>
>
> *In R the function I selected for my problem is optim.*
>
>
>
> *Below is my code  *
>
>
>
>
>
> *l = 2 # represent the number of mixture component*
>
> *i=1# represent the segment 1 if i=2 represent the 2 segment*
>
> *parametersDf #which I have posted above*
>
> *xnorm= function(x)*
>
> *{ *
>
>
>
> *  #observation= append(segment1, segment2)*
>
> *  mu.vector = parametersDf[1:l] *
>
> *  var.vector =parametersDf[(l+1):((2*l))]*
>
> *  coeff.vector=parametersDf[(2*l+1):(3*l)]*
>
> *  val_df=data.frame()*
>
> *  sum_prob=0*
>
> *  for (j in 1:l){*
>
> *
> val=(coeff.vector[i,j]*(dnorm(x,mu.vector[i,j],sqrt(var.vector[i,j]))))*
>
> *    sum_prob=sum_prob+val*
>
> *  } *
>
> *  return(sum_prob)*
>
> *}*
>
> *#segment1*
>
>
>
> *val1=optim(parametersDf$mean_mc_1[1],**  fn=xnorm,*
>
> *           method = "BFGS")*
>
>
>
> *I am not getting right result from optim function. Is there something I can
> do?*
>
>
> *Thanks in Advance for the help *
>
>       [[alternative HTML version deleted]]
>
> ______________________________________________
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> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.

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