RE: [R] Errors in Variables
On Sun, 29 May 2005, John Fox wrote: Dear Spencer, -Original Message- From: Spencer Graves [mailto:[EMAIL PROTECTED] Sent: Sunday, May 29, 2005 4:13 PM To: John Fox Cc: r-help@stat.math.ethz.ch; 'Jacob van Wyk'; 'Eric-Olivier Le Bigot' Subject: Re: [R] Errors in Variables Hi, John: Thanks for the clarification. I know that the errors in X problem requires additional information, most commonly one of the variances or the correlation. The question I saw (below) indicated he had tried model of the form y ~ x (with a given covariance matrix ...), which made me think of sem. If he wants the least (orthogonal) distance, could he could get it indirectly from sem by calling sem repeatedly giving, say, a variance for x, then averaging the variances of x and y and trying that in sem? I'm not sure how that would work, but seems similar to averaging the regressions of y on x and x on y. Also, what do you know about ODRpack? It looks like that might solve the least (orthogonal) distance. I'm not familiar with ODRpack, but it seems to me that one could fairly simply minimize the sum of squared least distances using, e.g., optim. Exactly. In fact this is easily reduced to a function of one variable (the slope, known to lie between the y or x and x om y regressions) and so optimize() would be more appropriate. I did do that in S once upon a long time, but it seemed too esoteric to package up (and it would take me longer to find the code than to do it again). My paper quoted originally deals with the case of known variances for each of x and y (and heteroscedasticity in both). It was written for chemists, and contains all the formulae one needs. In their applications knowing (at least approximately) the variances is a reasonable assumption. Brian Thanks again for your note, John. Best Wishes, Spencer Graves John Fox wrote: Dear Spencer, The reason that I didn't respond to the original posting (I'm the author of the sem package), that that without additional information (such as the error variance of x), a model with error in both x and y will be underidentified (unless there are multiple indicators of x, which didn't seem to be the case here). I figured that what Jacob had in mind was something like minimizing the least (orthogonal) distance of the points to the regression line (implying by the way that x and y are on the same scale or somehow standardized), which isn't doable with sem as far as I'm aware. Regards, John John Fox Department of Sociology McMaster University Hamilton, Ontario Canada L8S 4M4 905-525-9140x23604 http://socserv.mcmaster.ca/jfox -Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Spencer Graves Sent: Saturday, May 28, 2005 4:47 PM To: Eric-Olivier Le Bigot Cc: r-help@stat.math.ethz.ch; Jacob van Wyk Subject: Re: [R] Errors in Variables I'm sorry, I have not followed this thread, but I wonder if you have considered library(sem), structural equations modeling? Errors in variables problems are the canonical special case. Also, have you done a search of www.r-project.org - search - R site search for terms like errors in variables regression? This just led me to ODRpack, which is NOT a CRAN package but is apparently available after a Google search. If it were my problem, I'd first try to figure out sem; if that seemed too difficult, I might then look at ODRpack. Also, have you read the posting guide! http://www.R-project.org/posting-guide.html? This suggests, among other things, that you provide a toy example that a potential respondant could easily copy from your email, test a few modifications, and prase a reply in a minute or so. This also helps clarify your question so any respondants are more likely to suggest something that is actually useful to you. Moreover, many people have reported that they were able to answer their own question in the course of preparing a question for this list using the posting guide. hope this helps. spencer graves Eric-Olivier Le Bigot wrote: I'm interested in this 2D line fitting too! I've been looking, without success, in the list of R packages. It might be possible to implement quite easily some of the formalism that you can find in Numerical Recipes (Fortran 77, 2nd ed.), paragraph 15.3. As a matter of fact, I did this in R but only for a model of the form y ~ x (with a given covariance matrix between x and y). I can send you the R code (preliminary version: I wrote it yesterday), if you want. Another interesting reference might be Am. J. Phys. 60, p. 66 (1992). But, again, you would have to implement things by yourself. All the best, EOL -- Dr. Eric-Olivier LE BIGOT (EOL)CNRS Associate Researcher ~~~o~o
RE: [R] Errors in Variables
I have a routine that corrects regression coefficients for the bias towards zero that occurs when there is error in the measurement of the independent variable. The code only works for a single independent variable, i.e. y~x. At this time the program does not calculate the SE of the coefficient. The program uses properly weighted perpendicular least squares regression. I would be happy to share the code if asked to do so by anyone who has participated in this thread. John John Sorkin M.D., Ph.D. Chief, Biostatistics and Informatics Baltimore VA Medical Center GRECC and University of Maryland School of Medicine Claude Pepper OAIC University of Maryland School of Medicine Division of Gerontology Baltimore VA Medical Center 10 North Greene Street GRECC (BT/18/GR) Baltimore, MD 21201-1524 410-605-7119 - NOTE NEW EMAIL ADDRESS: [EMAIL PROTECTED] John Fox [EMAIL PROTECTED] 5/29/2005 5:56:10 PM Dear Spencer, -Original Message- From: Spencer Graves [mailto:[EMAIL PROTECTED] Sent: Sunday, May 29, 2005 4:13 PM To: John Fox Cc: r-help@stat.math.ethz.ch; 'Jacob van Wyk'; 'Eric-Olivier Le Bigot' Subject: Re: [R] Errors in Variables Hi, John: Thanks for the clarification. I know that the errors in X problem requires additional information, most commonly one of the variances or the correlation. The question I saw (below) indicated he had tried model of the form y ~ x (with a given covariance matrix ...), which made me think of sem. If he wants the least (orthogonal) distance, could he could get it indirectly from sem by calling sem repeatedly giving, say, a variance for x, then averaging the variances of x and y and trying that in sem? I'm not sure how that would work, but seems similar to averaging the regressions of y on x and x on y. Also, what do you know about ODRpack? It looks like that might solve the least (orthogonal) distance. I'm not familiar with ODRpack, but it seems to me that one could fairly simply minimize the sum of squared least distances using, e.g., optim. Regards, John Thanks again for your note, John. Best Wishes, Spencer Graves John Fox wrote: Dear Spencer, The reason that I didn't respond to the original posting (I'm the author of the sem package), that that without additional information (such as the error variance of x), a model with error in both x and y will be underidentified (unless there are multiple indicators of x, which didn't seem to be the case here). I figured that what Jacob had in mind was something like minimizing the least (orthogonal) distance of the points to the regression line (implying by the way that x and y are on the same scale or somehow standardized), which isn't doable with sem as far as I'm aware. Regards, John John Fox Department of Sociology McMaster University Hamilton, Ontario Canada L8S 4M4 905-525-9140x23604 http://socserv.mcmaster.ca/jfox -Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Spencer Graves Sent: Saturday, May 28, 2005 4:47 PM To: Eric-Olivier Le Bigot Cc: r-help@stat.math.ethz.ch; Jacob van Wyk Subject: Re: [R] Errors in Variables I'm sorry, I have not followed this thread, but I wonder if you have considered library(sem), structural equations modeling? Errors in variables problems are the canonical special case. Also, have you done a search of www.r-project.org - search - R site search for terms like errors in variables regression? This just led me to ODRpack, which is NOT a CRAN package but is apparently available after a Google search. If it were my problem, I'd first try to figure out sem; if that seemed too difficult, I might then look at ODRpack. Also, have you read the posting guide! http://www.R-project.org/posting-guide.html? This suggests, among other things, that you provide a toy example that a potential respondant could easily copy from your email, test a few modifications, and prase a reply in a minute or so. This also helps clarify your question so any respondants are more likely to suggest something that is actually useful to you. Moreover, many people have reported that they were able to answer their own question in the course of preparing a question for this list using the posting guide. hope this helps. spencer graves Eric-Olivier Le Bigot wrote: I'm interested in this 2D line fitting too! I've been looking, without success, in the list of R packages. It might be possible to implement quite easily some of the formalism that you can find in Numerical Recipes (Fortran 77, 2nd ed.), paragraph 15.3. As a matter of fact, I did this in R but only for a model of the form y ~ x (with a given covariance
RE: [R] Errors in Variables
Dear Spencer, The reason that I didn't respond to the original posting (I'm the author of the sem package), that that without additional information (such as the error variance of x), a model with error in both x and y will be underidentified (unless there are multiple indicators of x, which didn't seem to be the case here). I figured that what Jacob had in mind was something like minimizing the least (orthogonal) distance of the points to the regression line (implying by the way that x and y are on the same scale or somehow standardized), which isn't doable with sem as far as I'm aware. Regards, John John Fox Department of Sociology McMaster University Hamilton, Ontario Canada L8S 4M4 905-525-9140x23604 http://socserv.mcmaster.ca/jfox -Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Spencer Graves Sent: Saturday, May 28, 2005 4:47 PM To: Eric-Olivier Le Bigot Cc: r-help@stat.math.ethz.ch; Jacob van Wyk Subject: Re: [R] Errors in Variables I'm sorry, I have not followed this thread, but I wonder if you have considered library(sem), structural equations modeling? Errors in variables problems are the canonical special case. Also, have you done a search of www.r-project.org - search - R site search for terms like errors in variables regression? This just led me to ODRpack, which is NOT a CRAN package but is apparently available after a Google search. If it were my problem, I'd first try to figure out sem; if that seemed too difficult, I might then look at ODRpack. Also, have you read the posting guide! http://www.R-project.org/posting-guide.html? This suggests, among other things, that you provide a toy example that a potential respondant could easily copy from your email, test a few modifications, and prase a reply in a minute or so. This also helps clarify your question so any respondants are more likely to suggest something that is actually useful to you. Moreover, many people have reported that they were able to answer their own question in the course of preparing a question for this list using the posting guide. hope this helps. spencer graves Eric-Olivier Le Bigot wrote: I'm interested in this 2D line fitting too! I've been looking, without success, in the list of R packages. It might be possible to implement quite easily some of the formalism that you can find in Numerical Recipes (Fortran 77, 2nd ed.), paragraph 15.3. As a matter of fact, I did this in R but only for a model of the form y ~ x (with a given covariance matrix between x and y). I can send you the R code (preliminary version: I wrote it yesterday), if you want. Another interesting reference might be Am. J. Phys. 60, p. 66 (1992). But, again, you would have to implement things by yourself. All the best, EOL -- Dr. Eric-Olivier LE BIGOT (EOL)CNRS Associate Researcher ~~~o~o o~o~~~ Kastler Brossel Laboratory (LKB) http://www.lkb.ens.fr Université P. M. Curie and Ecole Normale Supérieure, Case 74 4 place Jussieu 75252 Paris CEDEX 05 France ~~~o~o o~o~~~ office : 01 44 27 73 67 fax: 01 44 27 38 45 ECR room: 01 44 27 47 12 x-ray room: 01 44 27 63 00 home: 01 73 74 61 87 For int'l calls: 33 + number without leading 0 On Wed, 25 May 2005, Jacob van Wyk wrote: I hope somebody can help. A student of mine is doing a study on Measurement Error models (errors-in-variables, total least squares, etc.). I have an old reference to a multi archive that contains leiv3: Programs for best line fitting with errors in both coordinates. (The date is October 1989, by B.D. Ripley et al.) I have done a search for something similar in R withour success. Has this been implemented in a R-package, possibly under some sort of assumptions about variances. I would lke my student to apply some regression techniques to data that fit this profile. Any help is much appreciated. (If I have not done my search more carefully - my apologies.) Thanks Jacob Jacob L van Wyk Department of Mathematics and Statistics University of Johannesburg APK P O Box 524 Auckland Park 2006 South Africa Tel: +27-11-489-3080 Fax: +27-11-489-2832 __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] Errors in Variables
Hi, John: Thanks for the clarification. I know that the errors in X problem requires additional information, most commonly one of the variances or the correlation. The question I saw (below) indicated he had tried model of the form y ~ x (with a given covariance matrix ...), which made me think of sem. If he wants the least (orthogonal) distance, could he could get it indirectly from sem by calling sem repeatedly giving, say, a variance for x, then averaging the variances of x and y and trying that in sem? Also, what do you know about ODRpack? It looks like that might solve the least (orthogonal) distance. Thanks again for your note, John. Best Wishes, Spencer Graves John Fox wrote: Dear Spencer, The reason that I didn't respond to the original posting (I'm the author of the sem package), that that without additional information (such as the error variance of x), a model with error in both x and y will be underidentified (unless there are multiple indicators of x, which didn't seem to be the case here). I figured that what Jacob had in mind was something like minimizing the least (orthogonal) distance of the points to the regression line (implying by the way that x and y are on the same scale or somehow standardized), which isn't doable with sem as far as I'm aware. Regards, John John Fox Department of Sociology McMaster University Hamilton, Ontario Canada L8S 4M4 905-525-9140x23604 http://socserv.mcmaster.ca/jfox -Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Spencer Graves Sent: Saturday, May 28, 2005 4:47 PM To: Eric-Olivier Le Bigot Cc: r-help@stat.math.ethz.ch; Jacob van Wyk Subject: Re: [R] Errors in Variables I'm sorry, I have not followed this thread, but I wonder if you have considered library(sem), structural equations modeling? Errors in variables problems are the canonical special case. Also, have you done a search of www.r-project.org - search - R site search for terms like errors in variables regression? This just led me to ODRpack, which is NOT a CRAN package but is apparently available after a Google search. If it were my problem, I'd first try to figure out sem; if that seemed too difficult, I might then look at ODRpack. Also, have you read the posting guide! http://www.R-project.org/posting-guide.html? This suggests, among other things, that you provide a toy example that a potential respondant could easily copy from your email, test a few modifications, and prase a reply in a minute or so. This also helps clarify your question so any respondants are more likely to suggest something that is actually useful to you. Moreover, many people have reported that they were able to answer their own question in the course of preparing a question for this list using the posting guide. hope this helps. spencer graves Eric-Olivier Le Bigot wrote: I'm interested in this 2D line fitting too! I've been looking, without success, in the list of R packages. It might be possible to implement quite easily some of the formalism that you can find in Numerical Recipes (Fortran 77, 2nd ed.), paragraph 15.3. As a matter of fact, I did this in R but only for a model of the form y ~ x (with a given covariance matrix between x and y). I can send you the R code (preliminary version: I wrote it yesterday), if you want. Another interesting reference might be Am. J. Phys. 60, p. 66 (1992). But, again, you would have to implement things by yourself. All the best, EOL -- Dr. Eric-Olivier LE BIGOT (EOL)CNRS Associate Researcher ~~~o~o o~o~~~ Kastler Brossel Laboratory (LKB) http://www.lkb.ens.fr Université P. M. Curie and Ecole Normale Supérieure, Case 74 4 place Jussieu 75252 Paris CEDEX 05 France ~~~o~o o~o~~~ office : 01 44 27 73 67 fax: 01 44 27 38 45 ECR room: 01 44 27 47 12 x-ray room: 01 44 27 63 00 home: 01 73 74 61 87 For int'l calls: 33 + number without leading 0 On Wed, 25 May 2005, Jacob van Wyk wrote: I hope somebody can help. A student of mine is doing a study on Measurement Error models (errors-in-variables, total least squares, etc.). I have an old reference to a multi archive that contains leiv3: Programs for best line fitting with errors in both coordinates. (The date is October 1989, by B.D. Ripley et al.) I have done a search for something similar in R withour success. Has this been implemented in a R-package, possibly under some sort of assumptions about variances. I would lke my student to apply some regression techniques to data that fit
RE: [R] Errors in Variables
Dear Spencer, -Original Message- From: Spencer Graves [mailto:[EMAIL PROTECTED] Sent: Sunday, May 29, 2005 4:13 PM To: John Fox Cc: r-help@stat.math.ethz.ch; 'Jacob van Wyk'; 'Eric-Olivier Le Bigot' Subject: Re: [R] Errors in Variables Hi, John: Thanks for the clarification. I know that the errors in X problem requires additional information, most commonly one of the variances or the correlation. The question I saw (below) indicated he had tried model of the form y ~ x (with a given covariance matrix ...), which made me think of sem. If he wants the least (orthogonal) distance, could he could get it indirectly from sem by calling sem repeatedly giving, say, a variance for x, then averaging the variances of x and y and trying that in sem? I'm not sure how that would work, but seems similar to averaging the regressions of y on x and x on y. Also, what do you know about ODRpack? It looks like that might solve the least (orthogonal) distance. I'm not familiar with ODRpack, but it seems to me that one could fairly simply minimize the sum of squared least distances using, e.g., optim. Regards, John Thanks again for your note, John. Best Wishes, Spencer Graves John Fox wrote: Dear Spencer, The reason that I didn't respond to the original posting (I'm the author of the sem package), that that without additional information (such as the error variance of x), a model with error in both x and y will be underidentified (unless there are multiple indicators of x, which didn't seem to be the case here). I figured that what Jacob had in mind was something like minimizing the least (orthogonal) distance of the points to the regression line (implying by the way that x and y are on the same scale or somehow standardized), which isn't doable with sem as far as I'm aware. Regards, John John Fox Department of Sociology McMaster University Hamilton, Ontario Canada L8S 4M4 905-525-9140x23604 http://socserv.mcmaster.ca/jfox -Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Spencer Graves Sent: Saturday, May 28, 2005 4:47 PM To: Eric-Olivier Le Bigot Cc: r-help@stat.math.ethz.ch; Jacob van Wyk Subject: Re: [R] Errors in Variables I'm sorry, I have not followed this thread, but I wonder if you have considered library(sem), structural equations modeling? Errors in variables problems are the canonical special case. Also, have you done a search of www.r-project.org - search - R site search for terms like errors in variables regression? This just led me to ODRpack, which is NOT a CRAN package but is apparently available after a Google search. If it were my problem, I'd first try to figure out sem; if that seemed too difficult, I might then look at ODRpack. Also, have you read the posting guide! http://www.R-project.org/posting-guide.html? This suggests, among other things, that you provide a toy example that a potential respondant could easily copy from your email, test a few modifications, and prase a reply in a minute or so. This also helps clarify your question so any respondants are more likely to suggest something that is actually useful to you. Moreover, many people have reported that they were able to answer their own question in the course of preparing a question for this list using the posting guide. hope this helps. spencer graves Eric-Olivier Le Bigot wrote: I'm interested in this 2D line fitting too! I've been looking, without success, in the list of R packages. It might be possible to implement quite easily some of the formalism that you can find in Numerical Recipes (Fortran 77, 2nd ed.), paragraph 15.3. As a matter of fact, I did this in R but only for a model of the form y ~ x (with a given covariance matrix between x and y). I can send you the R code (preliminary version: I wrote it yesterday), if you want. Another interesting reference might be Am. J. Phys. 60, p. 66 (1992). But, again, you would have to implement things by yourself. All the best, EOL -- Dr. Eric-Olivier LE BIGOT (EOL)CNRS Associate Researcher ~~~o~o o~o~~~ Kastler Brossel Laboratory (LKB) http://www.lkb.ens.fr Université P. M. Curie and Ecole Normale Supérieure, Case 74 4 place Jussieu 75252 Paris CEDEX 05 France ~~~o~o o~o~~~ office : 01 44 27 73 67 fax: 01 44 27 38 45 ECR room: 01 44 27 47 12 x-ray room: 01 44 27 63 00 home
Re: [R] Errors in Variables
I'm interested in this 2D line fitting too! I've been looking, without success, in the list of R packages. It might be possible to implement quite easily some of the formalism that you can find in Numerical Recipes (Fortran 77, 2nd ed.), paragraph 15.3. As a matter of fact, I did this in R but only for a model of the form y ~ x (with a given covariance matrix between x and y). I can send you the R code (preliminary version: I wrote it yesterday), if you want. Another interesting reference might be Am. J. Phys. 60, p. 66 (1992). But, again, you would have to implement things by yourself. All the best, EOL -- Dr. Eric-Olivier LE BIGOT (EOL)CNRS Associate Researcher ~~~o~oo~o~~~ Kastler Brossel Laboratory (LKB) http://www.lkb.ens.fr Université P. M. Curie and Ecole Normale Supérieure, Case 74 4 place Jussieu 75252 Paris CEDEX 05 France ~~~o~oo~o~~~ office : 01 44 27 73 67 fax: 01 44 27 38 45 ECR room: 01 44 27 47 12 x-ray room: 01 44 27 63 00 home: 01 73 74 61 87 For int'l calls: 33 + number without leading 0 On Wed, 25 May 2005, Jacob van Wyk wrote: I hope somebody can help. A student of mine is doing a study on Measurement Error models (errors-in-variables, total least squares, etc.). I have an old reference to a multi archive that contains leiv3: Programs for best line fitting with errors in both coordinates. (The date is October 1989, by B.D. Ripley et al.) I have done a search for something similar in R withour success. Has this been implemented in a R-package, possibly under some sort of assumptions about variances. I would lke my student to apply some regression techniques to data that fit this profile. Any help is much appreciated. (If I have not done my search more carefully - my apologies.) Thanks Jacob Jacob L van Wyk Department of Mathematics and Statistics University of Johannesburg APK P O Box 524 Auckland Park 2006 South Africa Tel: +27-11-489-3080 Fax: +27-11-489-2832 __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] Errors in Variables
I'm sorry, I have not followed this thread, but I wonder if you have considered library(sem), structural equations modeling? Errors in variables problems are the canonical special case. Also, have you done a search of www.r-project.org - search - R site search for terms like errors in variables regression? This just led me to ODRpack, which is NOT a CRAN package but is apparently available after a Google search. If it were my problem, I'd first try to figure out sem; if that seemed too difficult, I might then look at ODRpack. Also, have you read the posting guide! http://www.R-project.org/posting-guide.html? This suggests, among other things, that you provide a toy example that a potential respondant could easily copy from your email, test a few modifications, and prase a reply in a minute or so. This also helps clarify your question so any respondants are more likely to suggest something that is actually useful to you. Moreover, many people have reported that they were able to answer their own question in the course of preparing a question for this list using the posting guide. hope this helps. spencer graves Eric-Olivier Le Bigot wrote: I'm interested in this 2D line fitting too! I've been looking, without success, in the list of R packages. It might be possible to implement quite easily some of the formalism that you can find in Numerical Recipes (Fortran 77, 2nd ed.), paragraph 15.3. As a matter of fact, I did this in R but only for a model of the form y ~ x (with a given covariance matrix between x and y). I can send you the R code (preliminary version: I wrote it yesterday), if you want. Another interesting reference might be Am. J. Phys. 60, p. 66 (1992). But, again, you would have to implement things by yourself. All the best, EOL -- Dr. Eric-Olivier LE BIGOT (EOL)CNRS Associate Researcher ~~~o~oo~o~~~ Kastler Brossel Laboratory (LKB) http://www.lkb.ens.fr Université P. M. Curie and Ecole Normale Supérieure, Case 74 4 place Jussieu 75252 Paris CEDEX 05 France ~~~o~oo~o~~~ office : 01 44 27 73 67 fax: 01 44 27 38 45 ECR room: 01 44 27 47 12 x-ray room: 01 44 27 63 00 home: 01 73 74 61 87 For int'l calls: 33 + number without leading 0 On Wed, 25 May 2005, Jacob van Wyk wrote: I hope somebody can help. A student of mine is doing a study on Measurement Error models (errors-in-variables, total least squares, etc.). I have an old reference to a multi archive that contains leiv3: Programs for best line fitting with errors in both coordinates. (The date is October 1989, by B.D. Ripley et al.) I have done a search for something similar in R withour success. Has this been implemented in a R-package, possibly under some sort of assumptions about variances. I would lke my student to apply some regression techniques to data that fit this profile. Any help is much appreciated. (If I have not done my search more carefully - my apologies.) Thanks Jacob Jacob L van Wyk Department of Mathematics and Statistics University of Johannesburg APK P O Box 524 Auckland Park 2006 South Africa Tel: +27-11-489-3080 Fax: +27-11-489-2832 __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
[R] Errors in Variables
I hope somebody can help. A student of mine is doing a study on Measurement Error models (errors-in-variables, total least squares, etc.). I have an old reference to a multi archive that contains leiv3: Programs for best line fitting with errors in both coordinates. (The date is October 1989, by B.D. Ripley et al.) I have done a search for something similar in R withour success. Has this been implemented in a R-package, possibly under some sort of assumptions about variances. I would lke my student to apply some regression techniques to data that fit this profile. Any help is much appreciated. (If I have not done my search more carefully - my apologies.) Thanks Jacob Jacob L van Wyk Department of Mathematics and Statistics University of Johannesburg APK P O Box 524 Auckland Park 2006 South Africa Tel: +27-11-489-3080 Fax: +27-11-489-2832 __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
