Linda,
That depends on what you want to do. There are a number of packages dealing
with Markov type models: msm, depmix and hmm.discnp, and then there are all
the graphical models packages, some of which can do similar stuff.
Hth, ingmar
> From: "linda.s" <[EMAIL PROTECTED]>
> Date: Mon, 6 Feb 2006 03:37:13 -0800
> To: Ingmar Visser <[EMAIL PROTECTED]>
> Cc: Norman Goodacre <[EMAIL PROTECTED]>, <r-help@stat.math.ethz.ch>
> Subject: Re: [R] generating markov chain
>
> On 2/6/06, Ingmar Visser <[EMAIL PROTECTED]> wrote:
>> You can use the following, with x your transition matrix
>> y=numeric(100)
>> x=matrix(runif(16),4,4)
>> for(i in 2:100) {
>> y[i]=which(rmultinom(1, size = 1, prob = x[y[i-1], ])==1)
>> }
>> hth, ingmar
>>
>> -----Original Message-----
>> From: [EMAIL PROTECTED]
>> [mailto:[EMAIL PROTECTED] Behalf Of Norman Goodacre
>> Sent: maandag 6 februari 2006 5:26
>> To: r-help@stat.math.ethz.ch
>> Subject: [R] generating markov chain
>>
>>
>> Dear help group,
>>
>> Just fyi a markov chain is a sequence of transitions between states (say
>> A,T,G,C - on a gene) with a given probability for each transition. In this
>> case there'd be 16 different kinds, each with a different weight.
>> Given a transition matrix (4x4) filled with all transition probabilities
>> of course, how can I generate a random sequence of a given length, say 200?
>>
>> -Norman Goodacre
> Sorry, I am very new to this issue.
> Is there any tutorial to do Markov Chain?
> Thanks,
> Linda.
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