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I am looking to run diagnostics for categorical variable classifications in R. I am particularly interested in getting User's and Producer's accuracy and kappa statistics. There used to be a package (nnDiag) in R that calculated all of these metrics. It appears as if the package was removed from CRAN. Does anyone know why it was discontinued and if there is a comparable package in R? I am running R 3.1.1.
Caret does Cohen's Kappa and summary stats quite well.
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I want to run an estimation assuming that my variables are distributed according to the Dirichlet distribution. To do so, I need to use the cdf function. For all the distributions in R, there are the respective r,p and d functions that produce random variables, pdf and cdf.
Nevertheless, for the Dirichlet, I can only find the random number generator and the pdf.
Is there a similar package for R that gives the cdf?
Many thanks,
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Is there any package that you would recommend which can be used to calculate the precision, F1, recall for multi class classification task in R. I tried to use ROCR but it states that:
ROCR currently supports only evaluation of binary classification tasks
I know that you were looking for a solution in R. That said, this is a link to a nice solution library in Python, using scikit-learn version 0.14. Python is very similar to R in a lot of respects (if you haven't used it before), and this could be a good place to start.
Another place you might want to look, if you are focused on R, is the the PerfMeas package. As I quote, this "Package implements different performance measures for
classification and ranking tasks. AUC, precision at a given recall, F-score for single and multiple classes are available."
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Does any function in R (or Matlab) for the estimation of threshold vector autoregressive model (TVAR) by OLS for a number of threshold superior than 3?
In vgxvarx function, can I treat the 1st column of presample time series process matrix the threshold for my autoregressive model?
There are such functions in Econometrics Toolbox. Check out help vgxvarx.
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R provides a very powerful package called laplacesdemon for bayesian inference using the laplace distribution. I was wondering if there is any equivalent package for Matlab?
Thanks!
The question was a bit short so I'm not sure if this is exactly what you are asking for but here goes:
No - there is no Laplacedemon equivalent in Matlab
Yes - there are lots of Matlab packages that partly overlap with LaplaceDemon. As I don't know exactly what you want to do my recommendation is likely to have a high variance. Having established that I suggest that you take a look at http://becs.aalto.fi/en/research/bayes/gpstuff/ :). If you feel comfortable with using MCMC directly, you can take a look at http://helios.fmi.fi/~lainema/mcmc/. (I believe that matlab has some functions for this directly in their statistics or/and econometrics toolboxes)
You could also run R directly from Matlab http://neurochannels.blogspot.se/2010/05/how-to-run-r-code-in-matlab.html or http://rwiki.sciviews.org/doku.php?id=tips:callingr:matlab
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I'm doing a study on time series data of protein phosphorylation events, and I want to use dynamic bayesian network to learn the network structure. I found your Bayes net toolbox can be helpful for my study.But I'm more familiar with R. Is there any R packages equivalent to Matlab's Bayes net toolbox, which can learn the network structure using time series data? Thank you!
try the following R packages to perform dynamic bayesian networks inference:
http://cran.r-project.org/web/packages/G1DBN/index.html
and
http://cran.r-project.org/web/packages/ebdbNet/index.html
enjoy!