[R] Time Series on Binary Data.

[Cristiano Varin]

Among various possibilities, you might consider a logistic or probit regression model with ARMA errors specified via Gaussian copula. This approach is implemented in the package gcmr ("Gaussian Copula Marginal Regression").  

Example: logistic model with covariates S1 and S2 and AR(1,2) errors

fit <- gcmr( Response ~ S1 + S2 + ... , data = your.data, marginal = binomial.marg, cormat = arma.cormat(1,2), options( nrep=1000 ) )

See help(gcmr) for more details. 

Cristiano 
---------------------------------------------
Cristiano Varin <cristiano.varin at unive.it>
Department of Environmental Sciences, 
Informatics and Statistics
Ca' Foscari University of Venice
San Giobbe, Cannaregio 873, 30121 Venezia, Italy     
Tel: +39 0412347439   Fax: +39 0412347444
http://cristianovarin.weebly.com

> Hi,
> 
> I have a dichotomous data where some my independent variables are categorical, some are continuous and some are binary(0/1)
> 
> My dependent is a binary response (Fail/NoFail,0/1) .
> 
> The data is some readings collected everyday over a period of time.
> 
> The goal is to use this data and see if we can figure out cause of failure ,the end response.
> 
> Example data format
> 
> 
> Date, Type,Mileage,S1,S2,S3.... , Response
> 
> 03/02/2013,A,32000,1,0,1,......, 1
> 
> 03/03/2013,B,32400,0,0,0,.......,0
> 
> 03/04/2013,C,45000,0,1,1,......,1
> 
> 
> Can we do Time series modeling?? Any suggesstions on what type of other exploratory analysis can be used to figure out patterns in data ??
> 
> Thanks
> shi
>