[R] cleaning up a vector
I calculated a large vector. Unfortunately, I have some measurement error in my data and some of the values in the vector are erroneous. I ended up wih some Infs and NaNs in the vector. I would like to filter out the Inf and NaN values and only keep the values in my vector that range from 1 to 20. Is there a way to filter out Infs and NaNs in R and end up with a clean vector? Mike __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] [Fwd: Re: cleaning up a vector]
It turns out I didn't have to filter out the 1-20 values. The code of x[is.finite(x)] did the trick. Thanks!!! Mike Original Message Subject: Re: [R] cleaning up a vector From:Henrique Dallazuanna www...@gmail.com Date:Fri, October 1, 2010 1:55 pm To: mlar...@rsmas.miami.edu Cc: r-help@r-project.org -- Try this: x[is.finite(x)] On Fri, Oct 1, 2010 at 2:51 PM, mlar...@rsmas.miami.edu wrote: I calculated a large vector. Unfortunately, I have some measurement error in my data and some of the values in the vector are erroneous. I ended up wih some Infs and NaNs in the vector. I would like to filter out the Inf and NaN values and only keep the values in my vector that range from 1 to 20. Is there a way to filter out Infs and NaNs in R and end up with a clean vector? Mike __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. -- Henrique Dallazuanna Curitiba-Paraná-Brasil 25° 25' 40 S 49° 16' 22 O Try this: x[is.finite(x)] On Fri, Oct 1, 2010 at 2:51 PM, [1]mlar...@rsmas.miami.edu wrote: I calculated a large vector. Unfortunately, I have some measurement error in my data and some of the values in the vector are erroneous. I ended up wih some Infs and NaNs in the vector. I would like to filter out the Inf and NaN values and only keep the values in my vector that range from 1 to 20. Is there a way to filter out Infs and NaNs in R and end up with a clean vector? Mike __ [2]r-h...@r-project.org mailing list [3]https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide [4]http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. -- Henrique Dallazuanna Curitiba-Paraná-Brasil 25° 25' 40 S 49° 16' 22 O References 1. mailto:mlar...@rsmas.miami.edu 2. mailto:R-help@r-project.org 3. https://stat.ethz.ch/mailman/listinfo/r-help 4. http://www.R-project.org/posting-guide.html __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] maximum likelihood problem
I am trying to figure out how to run maximum likelihood in R. Here is my situation: I have the following equation: equation-(1/LR-(exp(-k*T)*LM)*(1-exp(-k))) LR, T, and LM are vectors of data. I want to R to change the value of k to maximize the value of equation. My attempts at optim and optimize have been unsuccessful. Are these the recommended functions that I should use to maximize my equation? With optim I wanted the function to be maximized so I had to make the fnscale negative. Here is what I put: L-optim(k,equation,control=(fnscale=-1)) My result: Error: could not find function fn Here is what I put for optimize: L-optimise(equation,k,maximum=TRUE) My result: Error: 'xmin' not less than 'xmax' Any advise would be greatly appreciated. Mike __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] [Fwd: RE: maximum likelihood problem]
I forgot to add that I first gave a starting value for K. Nonlinear least squares won't work because my errors are not normally distributed. Any advide on my maximum likelihood function would be greatly appreciated. Original Message Subject: RE: [R] maximum likelihood problem From:Ravi Varadhan rvarad...@jhmi.edu Date:Fri, October 1, 2010 5:10 pm To: mlar...@rsmas.miami.edu r-help@r-project.org -- Do you want to do a nonlinear least-squares estimation (which is MLE if the errors are Gaussian)? If so, you have to define a function that takes the parameter (k) and data matrix (LR, T, LM), as arguments, and returns a scalar, which is the residual sum of squares. Then you can optimize (minimize) that function. Ravi. -Original Message- From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On Behalf Of mlar...@rsmas.miami.edu Sent: Friday, October 01, 2010 4:40 PM To: r-help@r-project.org Subject: [R] maximum likelihood problem I am trying to figure out how to run maximum likelihood in R. Here is my situation: I have the following equation: equation-(1/LR-(exp(-k*T)*LM)*(1-exp(-k))) LR, T, and LM are vectors of data. I want to R to change the value of k to maximize the value of equation. My attempts at optim and optimize have been unsuccessful. Are these the recommended functions that I should use to maximize my equation? With optim I wanted the function to be maximized so I had to make the fnscale negative. Here is what I put: L-optim(k,equation,control=(fnscale=-1)) My result: Error: could not find function fn Here is what I put for optimize: L-optimise(equation,k,maximum=TRUE) My result: Error: 'xmin' not less than 'xmax' Any advise would be greatly appreciated. Mike __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
