[R] "Improvement with the R code"

[Elie Canonici Merle]

Ok, I assumed you wanted to compute a matrix M for all states such that

 M[i][j]= transition from state i to state j / number of transition from
state i

but from what you just answered it looks like you want to compute a matrix
M for a set of states S such that:
 M[S_i][S_j]= transition from state S_i to state S_j / number of transition
from state S_i    where S_i is in the set S
?

2017-08-28 17:50 GMT+02:00 niharika singhal <niharikasinghal1990 at gmail.com>:

> Sorry I have typed wrong value for output
> (2/6, 1/6, 3/6)
>
> On Mon, Aug 28, 2017 at 5:49 PM, niharika singhal <
> niharikasinghal1990 at gmail.com> wrote:
>
>> Hi Elie,
>>
>> Thanks for the mail
>>
>> If the number of states will change then the data frame will also have 4
>> as one of the value
>> Also I am only intersted in i and (i+1) (linear search for each state)
>>
>> in the above data frame for state1 ={1} the output will like
>> (1/6, 1/6, 3/6)
>>
>> Your code is giving me some error but I will see if I can remove and use
>> it.
>>
>> Regards
>> Niharika
>>
>> On Mon, Aug 28, 2017 at 5:31 PM, Elie Canonici Merle <
>> elie.canonicimerle at gmail.com> wrote:
>>
>>> Hi,
>>>
>>> I think you overthought this one a little bit, I don't know if this is
>>> the kind of code you are expecting but I came up with something like that:
>>>
>>> generate_transition_matrix <-  function(data, n_states) {
>>>
>>>     #To be sure I imagine you should check n_states is right at this
>>> point
>>>
>>>     transitions <- matrix(0, n_states, n_states)
>>>
>>>     #we could improve a little bit here because at step N+1 source is
>>> dest from step N
>>>     #but it would not be as readable
>>>     for (k in 1:(length(data) - 1)) {
>>>         source_state <- data[k]
>>>         dest_state <- data[k+1]
>>>         transitions[source_state, dest_state] <-
>>> transitions[source_state, dest_state] + 1
>>>     }
>>>
>>>     for (k in 1:n_states)
>>>         transitions[k,] <- transitions[k,] / sum(transitions[k,])
>>>     transitions
>>> }
>>>
>>> checkdf=data.frame(clusterNum=c(3,2,3,1,1,3,4,3,2,1,1,3,2,1,3,2))
>>> no_of_state=4
>>>
>>> transition_matrix= generate_transition_matrix(checkdf$clusterNum,
>>> no_of_state)
>>> transition_matrix
>>>
>>>
>>>
>>> 2017-08-28 16:37 GMT+02:00 niharika singhal <
>>> niharikasinghal1990 at gmail.com>:
>>>
>>>> Hello,
>>>>
>>>> I am trying to implement a formula
>>>>
>>>>  aij= transition from state S_i to S_j/no of transition at state S_i
>>>>
>>>>
>>>>
>>>> Code I have written is working with three state {1,2,3 }, but if the
>>>> number
>>>> of states become={1,2,3,4,......n} then the code will not work, so can
>>>> some
>>>> help me with this.
>>>>
>>>> For   and some rows of my  data frame look like
>>>>
>>>> checkdf=data.frame(clusterNum=c(3,2,3,1,1,3,4,3,2,1,1,3,2,1,3,2)
>>>> no_of_state=3
>>>> transition_matrix=matrix(NA,nrow=no_of_state, ncol=no_of_state)
>>>> for(k in 1: no_of_state)
>>>> {
>>>>   count1=0
>>>>   count2=0
>>>>   count3=0
>>>>   #For last point no transition takes place
>>>>   for(j in 1: (nrow(checkdf)-1))
>>>>   {
>>>>
>>>>     if(checkdf$clusterNum[j]==k)
>>>>     {
>>>>       if(checkdf$clusterNum[j+1]==1){
>>>>         count1=count1+1
>>>>       }
>>>>       else if(checkdf$clusterNum[j+1]==2){
>>>>         count2=count2+1
>>>>        }
>>>>       else {
>>>>         count3=count3+1
>>>>        }
>>>>     }
>>>>   }
>>>>
>>>>   no_of_points=(count1+count2+count3)
>>>>   s1=count1/no_of_points
>>>>   s2=count2/no_of_points
>>>>   s3=count3/no_of_points
>>>>   transition_matrix[k,]=c(s1, s2, s3)
>>>>
>>>> }
>>>>
>>>> I know the code is not written nicely and I want to improve it.
>>>>
>>>> Thanks in advance
>>>> Niharika
>>>>
>>>>         [[alternative HTML version deleted]]
>>>>
>>>> ______________________________________________
>>>> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
>>>> https://stat.ethz.ch/mailman/listinfo/r-help
>>>> PLEASE do read the posting guide http://www.R-project.org/posti
>>>> ng-guide.html
>>>> and provide commented, minimal, self-contained, reproducible code.
>>>>
>>>
>>>
>>
>

	[[alternative HTML version deleted]]