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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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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 a package in R that allows me to plot multiply time series next to each other 3D?
Like in the following examples:
http://farm6.staticflickr.com/5142/5619005462_5eab3c8cdd_b.jpg
http://synoptic.weaintplastic.com/
Thanks
Have you checked out chartSeries3d0 from the quantmod package?
Here's an example I found on quantmod.com:
library(quantmod)
source("http://www.quantmod.com/examples/chartSeries3d/chartSeries3d.alpha.R")
getSymbols("DGS1MO;DGS3MO;DGS6MO;DGS1;DGS2;DGS3;DGS5;DGS7;DGS10;DGS20;DGS30",src="FRED")
TR <- merge(DGS1MO,DGS3MO,DGS6MO,DGS1,DGS2,DGS3,DGS5,DGS7,DGS10,DGS20,DGS30, all=FALSE)
colnames(TR) <- c("1mo","3mo","6mo","1yr","2yr","3yr","5yr","7yr","10yr","20yr","30yr")
TR <- na.locf(TR)
chartSeries3d0(TR["2011"])
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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!
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Is there any scripting language function (like in python or bash) that samples from a zipf-like distribution, for exponent 0<a<=1. Zipf-like distribution p(a) can be found, here.
PS: I am aware of existence of numpy function that can generate zipf samples, but it's only for a >1.