[R] geotiff calculations
Dear list, I have to compare two digital elevation models in raster format (geotiff). I then have to calculate the differences in altitude for each cell and make some statistics (basic as mean, median, std, range but also more advanced as RMSE) on that. I do not know very much how to proceed: 1) is it possible to import the geotiff in R? If so with which package? if not which is the best way to import such files? 2) is it better to perform the calculations of the differences in a GIS software and then to use R only for statistical analysis? or it is better to do everything in R? 3) is there any specific package for doing this kind of analysis? Thank you very much in advance Laura [[alternative HTML version deleted]] __ 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] R function, sink() and empty file
Dear all,
I wrote a simple script in order to put together some functions and method
to be executed on various files
I am trying to have to possibility to call the script changing few
parameters in order to use the different files.
I succeeded partly using the function method.
However in my script I call the sink() function in order to output the
results to a .txt file. When using the function the file is empty, when
running the script manually the file is fine. How can I solve that?
Is there any other way to run a R script on different files with different
names?
Thank you very much in advance
Laura
=
EXAMPLE OF CODE
=
km = function(a,o) {
fld - system.file(G:/ALRPC/JRC/IMG/, package=rgdal)
filename = as.name(paste (a, -, o, sep=))
file - read.table(paste(R_out/, filename, .txt, sep=))
obj - kmenas(file, 5)
sink(paste(R_out/res, filename, .txt, sep=))
Kluster centers
obj$centers
Within size for clusters
obj$withinss
Cluster size
obj$size
sink()
}
[[alternative HTML version deleted]]
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and provide commented, minimal, self-contained, reproducible code.
[R] cluster.stats
Dear list, I just tried to use the function cluster.stat in the package fpc. I just have a couple of questions about the syntax: cluster.stats(d,clustering,alt.clustering=NULL, silhouette=TRUE,G2=FALSE,G3=FALSE) 1) the distance object (d) is an object obtained by the function dist() on my own original matrix? 2) clustering is the clusters vector as result of one of the many clustering methods? Thank you very much in advance and sorry for such basic question, but I did not manage to clarify my mind. Laura [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] cluster.stats
Thank you very much for your answer. I tried to run the function on my data and now I am getting this message of error Error in as.dist(dmat[clustering == i, clustering == i]) : (subscript) logical subscript too long Below the code I am using (version2.7.0 of R with all packages updated): data - - as(img, data.frame)[1:1]#(where img is a small image 256 px x 256 px) kl - kmeans(data, 5) library(fpc) cluster.stats(data, kl$cluster) Thank you for any hints on the reasons and meaning of the error! Laura 2008/6/13 Christian Hennig [EMAIL PROTECTED]: Dear Laura, Dear list, I just tried to use the function cluster.stat in the package fpc. I just have a couple of questions about the syntax: cluster.stats(d,clustering,alt.clustering=NULL, silhouette=TRUE,G2=FALSE,G3=FALSE) 1) the distance object (d) is an object obtained by the function dist() on my own original matrix? d is allowed to be an object of class dist or a dissimilarity matrix. The answer to your question depends on what your original matrix is. If it is something on which you can compute a distance by dist(), you're right, at least if dist() delivers the distance you are interested in. 2) clustering is the clusters vector as result of one of the many clustering methods? The help page tells you what clustering can be. So it could be the clustering/partition vector of a clustering method or it could be something else. Note that cluster.stats doesn't depend on any particular clustering method. It computes the statistics regardless of where the clustering vector comes from. Best regards, Christian Thank you very much in advance and sorry for such basic question, but I did not manage to clarify my mind. Laura [[alternative HTML version deleted]] __ 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. *** --- *** Christian Hennig University College London, Department of Statistical Science Gower St., London WC1E 6BT, phone +44 207 679 1698 [EMAIL PROTECTED], www.homepages.ucl.ac.uk/~ucakchehttp://www.homepages.ucl.ac.uk/%7Eucakche [[alternative HTML version deleted]] __ 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.
Re: [R] cluster.stats
I am sorry I did not provide enough information. I am not using img later, but data that is data.frame. I wrote that img is a image just to explain what kind of data is coming from, but the object I am using is data and it is a data.frame (checked many times). I am not using as.dist, but dist in order to calculate the distance matrix among the data I have. Then the whole code I am using is: data - - as(img, data.frame)[1:1]#(where img is an image 256x256 px) kl - kmeans(data, 5) library(fpc) ddata - dist(data) dcent - dist(kl$centers) cluster.stats(ddata, kl$cluster) cluster.stats(dcent, kl$cluster) In both cases I got the same error: Error in as.dist(dmat[clustering == i, clustering == i]) : (subscript) logical subscript too long Below the structure of the different objects is detailed below: data is 'data.frame': 262144 obs. of 1 variable kl$centers is num [1:5, 1] kl$cluster is Named int [1:262144] I hope it is more informative. I am sorry but I did not find any explanation for the error message I am getting. Thank you very much in advance Laura 2008/6/14 Christian Hennig [EMAIL PROTECTED]: The given information is not enough to tell you what's going on. as.dist doesn't appear in the given code and it's not clear to me what kind of object img is (a small image doesn't tell me what R makes of it). Also, try to read the help pages first and find out whether img is of the format that is required by the functions. And check (using str for example) whether data is what you expect it to be. Christian On Sat, 14 Jun 2008, Laura Poggio wrote: Thank you very much for your answer. I tried to run the function on my data and now I am getting this message of error Error in as.dist(dmat[clustering == i, clustering == i]) : (subscript) logical subscript too long Below the code I am using (version2.7.0 of R with all packages updated): data - - as(img, data.frame)[1:1]#(where img is a small image 256 px x 256 px) kl - kmeans(data, 5) library(fpc) cluster.stats(data, kl$cluster) Thank you for any hints on the reasons and meaning of the error! Laura 2008/6/13 Christian Hennig [EMAIL PROTECTED]: Dear Laura, Dear list, I just tried to use the function cluster.stat in the package fpc. I just have a couple of questions about the syntax: cluster.stats(d,clustering,alt.clustering=NULL, silhouette=TRUE,G2=FALSE,G3=FALSE) 1) the distance object (d) is an object obtained by the function dist() on my own original matrix? d is allowed to be an object of class dist or a dissimilarity matrix. The answer to your question depends on what your original matrix is. If it is something on which you can compute a distance by dist(), you're right, at least if dist() delivers the distance you are interested in. 2) clustering is the clusters vector as result of one of the many clustering methods? The help page tells you what clustering can be. So it could be the clustering/partition vector of a clustering method or it could be something else. Note that cluster.stats doesn't depend on any particular clustering method. It computes the statistics regardless of where the clustering vector comes from. Best regards, Christian Thank you very much in advance and sorry for such basic question, but I did not manage to clarify my mind. Laura [[alternative HTML version deleted]] __ 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. *** --- *** Christian Hennig University College London, Department of Statistical Science Gower St., London WC1E 6BT, phone +44 207 679 1698 [EMAIL PROTECTED], www.homepages.ucl.ac.uk/~ucakchehttp://www.homepages.ucl.ac.uk/%7Eucakche http://www.homepages.ucl.ac.uk/%7Eucakche *** --- *** Christian Hennig University College London, Department of Statistical Science Gower St., London WC1E 6BT, phone +44 207 679 1698 [EMAIL PROTECTED], www.homepages.ucl.ac.uk/~ucakchehttp://www.homepages.ucl.ac.uk/%7Eucakche [[alternative HTML version deleted]] __ 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.
Re: [R] cluster.stats
Thank. See below. Laura 2008/6/14 Christian Hennig [EMAIL PROTECTED]: What does str(ddata) give? Class 'dist' atomic [1:130816] 69.2 117.1 145.6 179.9 195.6 ... dcent doesn't make sense as input for cluster.stats, because you need a dissimilarity matrix between all objects. Yes I know ... I simply try to see if something was changing with different structure of data Christian On Sat, 14 Jun 2008, Laura Poggio wrote: I am sorry I did not provide enough information. I am not using img later, but data that is data.frame. I wrote that img is a image just to explain what kind of data is coming from, but the object I am using is data and it is a data.frame (checked many times). I am not using as.dist, but dist in order to calculate the distance matrix among the data I have. Then the whole code I am using is: data - - as(img, data.frame)[1:1]#(where img is an image 256x256 px) kl - kmeans(data, 5) library(fpc) ddata - dist(data) dcent - dist(kl$centers) cluster.stats(ddata, kl$cluster) cluster.stats(dcent, kl$cluster) In both cases I got the same error: Error in as.dist(dmat[clustering == i, clustering == i]) : (subscript) logical subscript too long Below the structure of the different objects is detailed below: data is 'data.frame': 262144 obs. of 1 variable kl$centers is num [1:5, 1] kl$cluster is Named int [1:262144] I hope it is more informative. I am sorry but I did not find any explanation for the error message I am getting. Thank you very much in advance Laura 2008/6/14 Christian Hennig [EMAIL PROTECTED]: The given information is not enough to tell you what's going on. as.dist doesn't appear in the given code and it's not clear to me what kind of object img is (a small image doesn't tell me what R makes of it). Also, try to read the help pages first and find out whether img is of the format that is required by the functions. And check (using str for example) whether data is what you expect it to be. Christian On Sat, 14 Jun 2008, Laura Poggio wrote: Thank you very much for your answer. I tried to run the function on my data and now I am getting this message of error Error in as.dist(dmat[clustering == i, clustering == i]) : (subscript) logical subscript too long Below the code I am using (version2.7.0 of R with all packages updated): data - - as(img, data.frame)[1:1]#(where img is a small image 256 px x 256 px) kl - kmeans(data, 5) library(fpc) cluster.stats(data, kl$cluster) Thank you for any hints on the reasons and meaning of the error! Laura 2008/6/13 Christian Hennig [EMAIL PROTECTED]: Dear Laura, Dear list, I just tried to use the function cluster.stat in the package fpc. I just have a couple of questions about the syntax: cluster.stats(d,clustering,alt.clustering=NULL, silhouette=TRUE,G2=FALSE,G3=FALSE) 1) the distance object (d) is an object obtained by the function dist() on my own original matrix? d is allowed to be an object of class dist or a dissimilarity matrix. The answer to your question depends on what your original matrix is. If it is something on which you can compute a distance by dist(), you're right, at least if dist() delivers the distance you are interested in. 2) clustering is the clusters vector as result of one of the many clustering methods? The help page tells you what clustering can be. So it could be the clustering/partition vector of a clustering method or it could be something else. Note that cluster.stats doesn't depend on any particular clustering method. It computes the statistics regardless of where the clustering vector comes from. Best regards, Christian Thank you very much in advance and sorry for such basic question, but I did not manage to clarify my mind. Laura [[alternative HTML version deleted]] __ 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. *** --- *** Christian Hennig University College London, Department of Statistical Science Gower St., London WC1E 6BT, phone +44 207 679 1698 [EMAIL PROTECTED], www.homepages.ucl.ac.uk/~ucakchehttp://www.homepages.ucl.ac.uk/%7Eucakche http://www.homepages.ucl.ac.uk/%7Eucakche http://www.homepages.ucl.ac.uk/%7Eucakche *** --- *** Christian Hennig University College London, Department of Statistical Science Gower St., London WC1E 6BT, phone +44 207 679 1698 [EMAIL PROTECTED], www.homepages.ucl.ac.uk/~ucakchehttp://www.homepages.ucl.ac.uk/%7Eucakche http://www.homepages.ucl.ac.uk/%7Eucakche *** --- *** Christian Hennig University College London, Department of Statistical Science Gower St., London WC1E 6BT, phone +44 207 679 1698 [EMAIL PROTECTED], www.homepages.ucl.ac.uk/~ucakchehttp
Re: [R] cluster.stats
Thank you very much for all the info and support. Now I managed to make it working on a small subset of the original data set. I think that the first error message I got (Error in as.dist(dmat[clustering == i, clustering == i]) : (subscript) logical subscript too long) is generated when the 2 objects required by cluster.stats do not have the same length. Thanks! Laura --- Original message --- Da: Christian Hennig [EMAIL PROTECTED] Inviato: 14.6.'08, 20:46 Dear Laura, I have R 2.6.0. I tried dist on a vector of length 200,000 and it told me that it is too long. Theoretically, if you have 260,000 observations, the length of the dist object should be 260,000*259,999/2, which is too large for our computers, I guess. Which means that unfortunately cluster.stats won't work for such a large data set, because it needs the full casewise dissimilarity information. I don't understand how you managed to produce a dist object of length of only 130,000 out of your data, but it certainly doesn't give all pairwise distance information for 260,000 points and therefore cannot be used in cluster.stats with a clustering vector of length 260,000 or so. Sorry, Christian On Sat, 14 Jun 2008, Laura Poggio wrote: Thank. See below. Laura 2008/6/14 Christian Hennig [EMAIL PROTECTED]: What does str(ddata) give? Class 'dist' atomic [1:130816] 69.2 117.1 145.6 179.9 195.6 ... dcent doesn't make sense as input for cluster.stats, because you need a dissimilarity matrix between all objects. Yes I know ... I simply try to see if something was changing with different structure of data Christian On Sat, 14 Jun 2008, Laura Poggio wrote: I am sorry I did not provide enough information. I am not using img later, but data that is data.frame. I wrote that img is a image just to explain what kind of data is coming from, but the object I am using is data and it is a data.frame (checked many times). I am not using as.dist, but dist in order to calculate the distance matrix among the data I have. Then the whole code I am using is: data - - as(img, data.frame)[1:1]#(where img is an image 256x256 px) kl - kmeans(data, 5) library(fpc) ddata - dist(data) dcent - dist(kl$centers) cluster.stats(ddata, kl$cluster) cluster.stats(dcent, kl$cluster) In both cases I got the same error: Error in as.dist(dmat[clustering == i, clustering == i]) : (subscript) logical subscript too long Below the structure of the different objects is detailed below: data is 'data.frame': 262144 obs. of 1 variable kl$centers is num [1:5, 1] kl$cluster is Named int [1:262144] I hope it is more informative. I am sorry but I did not find any explanation for the error message I am getting. Thank you very much in advance Laura 2008/6/14 Christian Hennig [EMAIL PROTECTED]: The given information is not enough to tell you what's going on. as.dist doesn't appear in the given code and it's not clear to me what kind of object img is (a small image doesn't tell me what R makes of it). Also, try to read the help pages first and find out whether img is of the format that is required by the functions. And check (using str for example) whether data is what you expect it to be. Christian On Sat, 14 Jun 2008, Laura Poggio wrote: Thank you very much for your answer. I tried to run the function on my data and now I am getting this message of error Error in as.dist(dmat[clustering == i, clustering == i]) : (subscript) logical subscript too long Below the code I am using (version2.7.0 of R with all packages updated): data - - as(img, data.frame)[1:1]#(where img is a small image 256 px x 256 px) kl - kmeans(data, 5) library(fpc) cluster.stats(data, kl$cluster) Thank you for any hints on the reasons and meaning of the error! Laura 2008/6/13 Christian Hennig [EMAIL PROTECTED]: Dear Laura, Dear list, I just tried to use the function cluster.stat in the package fpc. I just have a couple of questions about the syntax: cluster.stats(d,clustering,alt.clustering=NULL, silhouette=TRUE,G2=FALSE,G3=FALSE) 1) the distance object (d) is an object obtained by the function dist() on my own original matrix? d is allowed to be an object of class dist or a dissimilarity matrix. The answer to your question depends on what your original matrix is. If it is something on which you can compute a distance by dist(), you're right, at least if dist() delivers the distance you are interested in. 2) clustering is the clusters vector as result of one of the many clustering methods? The help page tells you what clustering can be. So it could be the clustering/partition vector of a clustering method or it could be something else. Note that cluster.stats doesn't depend on any
[R] variable as part of file name
Dear all, sorry for this very basic question, but I did not find any good example yet. I would like to set up a variable that can be recall later to substitute a part of a file name. As example: var_filename = as.name(aaa) jpeg(var_filename.jpg) plot() dev.off() It would be very useful in order to avoid to change manually many strings. I guess it is possible, but I did not find a way. I am using R 2.7.0 on a window machine. Thank you very much in advance. Laura [[alternative HTML version deleted]] __ 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.
Re: [R] variable as part of file name
Thank you perfect! it worked also with the GDAL option. Laura 2008/7/2 Richard Pearson [EMAIL PROTECTED]: Laura Does jpeg(paste(var_filename, jpg, sep=.)) do what you want? Regards Richard Laura Poggio wrote: Dear all, sorry for this very basic question, but I did not find any good example yet. I would like to set up a variable that can be recall later to substitute a part of a file name. As example: var_filename = as.name(aaa) jpeg(var_filename.jpg) plot() dev.off() It would be very useful in order to avoid to change manually many strings. I guess it is possible, but I did not find a way. I am using R 2.7.0 on a window machine. Thank you very much in advance. Laura [[alternative HTML version deleted]] __ 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. -- Richard D. Pearson [EMAIL PROTECTED] School of Computer Science, http://www.cs.man.ac.uk/~pearsonrhttp://www.cs.man.ac.uk/%7Epearsonr University of Manchester, Tel: +44 161 275 6178 Oxford Road, Mob: +44 7971 221181 Manchester M13 9PL, UK.Fax: +44 161 275 6204 [[alternative HTML version deleted]] __ 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] x axe values
Dear list, I have to draw a simple plot. On y axe some numerical values that correspond to various categories on axe x. The table I am reading looks like: cat Obj1 Obj2 Obj3 max 23 27 34 ave 21 25 32 min 19 23 30 In order to avoid that the first column is reordered alphabetically I used: (found here http://tolstoy.newcastle.edu.au/R/help/06/09/33808.html) a - as.character(table$cat) table$cat = factor(a, levels=a) However if I use plot() I get thick lines instead of points because of the reason explained in the link above. If I use plot.default() I get number on the x axe instead of the name of the categories. 1) first question: any solution? An alternative could be to use plot.default() and then to change the value on the axe. 2) second question: how to chnage the value of the axes? not the label, but the values themself? Thank you very much in advance Laura [[alternative HTML version deleted]] __ 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.
Re: [R] R-square in robust regression
yes thank you! it is perfect. I was using lmrob in package robustbase and it did not have that option in the summary. Laura 2008/11/13 Mark Difford [EMAIL PROTECTED] Hi Laura, I was searching for a way to compute robust R-square in R in order to get an information similar to the Proportion of variation in response(s) explained by model(s) computed by S-Plus. There are several options. I have had good results using wle.lm() in package wle and lmRob() in package robust. The second option is perhaps closest to what you want. Regards, Mark. Laura POggio wrote: I was searching for a way to compute robust R-square in R in order to get an information similar to the Proportion of variation in response(s) explained by model(s) computed by S-Plus. This post is dealing with that. Would be possible to have some hints on how to calculate this parameter within R? Thank you very much in advance. Laura Poggio - Date: Mon, 20 Oct 2008 06:15:49 +0100 (BST) From: Prof Brian Ripley [EMAIL PROTECTED] Subject: Re: [R] R-square in robust regression To: PARKERSO [EMAIL PROTECTED] Cc: r-help@r-project.org Message-ID: [EMAIL PROTECTED] Content-Type: TEXT/PLAIN; charset=US-ASCII; format=flowed On Sun, 19 Oct 2008, PARKERSO wrote: Hi there, I have just started using the MASS package in R to run M-estimator robust regressions. The final output appears to only give coefficients, degrees of freedom and t-stats. Does anyone know why R doesn't compute R or R-squared These as only valid for least-squares fits -- they will include the possible outliers in the measure of fit. And BTW, it is not 'R', but the uncredited author of the package who made such design decisions. and why doesn't give you any other indices of goodness of fit? Which ones did you have in mind? It does give a scale estimate of the residuals, and this determines the predition accuracy. Does anyone know how to compute these in R? Yes. Sophie -- Brian D. Ripley, [EMAIL PROTECTED] Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/http://www.stats.ox.ac.uk/%7Eripley/ http://www.stats.ox.ac.uk/%7Eripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UKFax: +44 1865 272595 [[alternative HTML version deleted]] __ 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. -- View this message in context: http://www.nabble.com/Re%3A-R-square-in-robust-regression-tp20478161p20478307.html Sent from the R help mailing list archive at Nabble.com. __ 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. [[alternative HTML version deleted]] __ 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.
Re: [R] R-square in robust regression
I was searching for a way to compute robust R-square in R in order to get an information similar to the Proportion of variation in response(s) explained by model(s) computed by S-Plus. This post is dealing with that. Would be possible to have some hints on how to calculate this parameter within R? Thank you very much in advance. Laura Poggio - Date: Mon, 20 Oct 2008 06:15:49 +0100 (BST) From: Prof Brian Ripley [EMAIL PROTECTED] Subject: Re: [R] R-square in robust regression To: PARKERSO [EMAIL PROTECTED] Cc: r-help@r-project.org Message-ID: [EMAIL PROTECTED] Content-Type: TEXT/PLAIN; charset=US-ASCII; format=flowed On Sun, 19 Oct 2008, PARKERSO wrote: Hi there, I have just started using the MASS package in R to run M-estimator robust regressions. The final output appears to only give coefficients, degrees of freedom and t-stats. Does anyone know why R doesn't compute R or R-squared These as only valid for least-squares fits -- they will include the possible outliers in the measure of fit. And BTW, it is not 'R', but the uncredited author of the package who made such design decisions. and why doesn't give you any other indices of goodness of fit? Which ones did you have in mind? It does give a scale estimate of the residuals, and this determines the predition accuracy. Does anyone know how to compute these in R? Yes. Sophie -- Brian D. Ripley, [EMAIL PROTECTED] Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/http://www.stats.ox.ac.uk/%7Eripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UKFax: +44 1865 272595 [[alternative HTML version deleted]] __ 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.
Re: [R] R-square in robust regression
I am aware of the limits of the parameter R^2 in this case. However often it is required for many different reasons. And it is helpful to have a function that does it. The most important is to know the drawback of thenumber, I think. Laura 2008/11/13 Martin Maechler [EMAIL PROTECTED] LP == Laura Poggio [EMAIL PROTECTED] on Thu, 13 Nov 2008 10:43:14 + writes: LP yes thank you! it is perfect. LP I was using lmrob in package robustbase and it did not have that option in LP the summary. Yes lmRob() from robust is from a company which -- often being excellent -- has at times listened much more to its not-so-professional customers instead of its expert advisors. So, yes indeed, summary(lmRob(..)) happily reports something like Multiple R-Squared: 0.620538 (number: for the stack loss example) But the question is if the customer should get R^2 even in casses where its definition is very doubtful and indeed somewhat *counter* to the purpose of using methods that are NOT least-squares based Martin Maechler, ETH Zurich LP 2008/11/13 Mark Difford [EMAIL PROTECTED] Hi Laura, I was searching for a way to compute robust R-square in R in order to get an information similar to the Proportion of variation in response(s) explained by model(s) computed by S-Plus. There are several options. I have had good results using wle.lm() in package wle and lmRob() in package robust. The second option is perhaps closest to what you want. Regards, Mark. Laura POggio wrote: I was searching for a way to compute robust R-square in R in order to get an information similar to the Proportion of variation in response(s) explained by model(s) computed by S-Plus. This post is dealing with that. Would be possible to have some hints on how to calculate this parameter within R? Thank you very much in advance. Laura Poggio - Date: Mon, 20 Oct 2008 06:15:49 +0100 (BST) From: Prof Brian Ripley [EMAIL PROTECTED] Subject: Re: [R] R-square in robust regression To: PARKERSO [EMAIL PROTECTED] Cc: r-help@r-project.org Message-ID: [EMAIL PROTECTED] Content-Type: TEXT/PLAIN; charset=US-ASCII; format=flowed On Sun, 19 Oct 2008, PARKERSO wrote: Hi there, I have just started using the MASS package in R to run M-estimator robust regressions. The final output appears to only give coefficients, degrees of freedom and t-stats. Does anyone know why R doesn't compute R or R-squared These as only valid for least-squares fits -- they will include the possible outliers in the measure of fit. And BTW, it is not 'R', but the uncredited author of the package who made such design decisions. and why doesn't give you any other indices of goodness of fit? Which ones did you have in mind? It does give a scale estimate of the residuals, and this determines the predition accuracy. Does anyone know how to compute these in R? Yes. Sophie -- Brian D. Ripley, [EMAIL PROTECTED] Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/http://www.stats.ox.ac.uk/%7Eripley/ http://www.stats.ox.ac.uk/%7Eripley/ http://www.stats.ox.ac.uk/%7Eripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UKFax: +44 1865 272595 [[alternative HTML version deleted]] __ 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. -- View this message in context: http://www.nabble.com/Re%3A-R-square-in-robust-regression-tp20478161p20478307.html Sent from the R help mailing list archive at Nabble.com. __ 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. LP [[alternative HTML version deleted]] LP __ LP R-help@r-project.org mailing list LP https://stat.ethz.ch/mailman/listinfo/r-help LP PLEASE do read the posting guide http://www.R-project.org
