[R] Panel regression in R
I am currently trying to replicate the results I got
from RATS for a panel regression. The codes in RATS
looks like this:
* Final equation for Office Cap Rate Spread
* Regression, Panel Data
preg(effects=time, method=random) CapRate
# CapRate{1} RentCycle{1} VacancyChangeYTY
InflationYTY RealGDPyty
Just wonder what R package also allow me to have the
options like (effects=time, method=random). Could
anyone share some thoughts with me? Any input will be
helpful. Thank you very much!
Best,
Ed.
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[R] How to do log normal regression?
I want to fit a Log-Normal CDF function between two variables, and estimate the parameters. Is there any package/functions designed for this purpose? Basically, I have data for Y and X, and I suspect the relationship between Y and X is Y = CDF Log-Normal (X), and I want to run this regression to verify this and estimate the parameters. Anyone has any thoughts? Any input is valuable to me, so please do not hesitate to share your thoughts. Thank you! Ed. __ 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 with non-integer #successes in a binomial glm
Hi, I had a logit regression, but don't really know how to handle the Warning message: non-integer #successes in a binomial glm! in: eval(expr, envir, enclos) problem. I had the same logit regression without weights and it worked out without the warning, but I figured it makes more sense to add the weights. The weights sum up to one. Could anyone give me some hint? Thanks a lot! FYI, I have posted both regressions (with and without weights) below. Ed setwd(P:/Work in Progress/Haibo/Hans) Lease=read.csv(lease.csv, header=TRUE) Lease$ET - factor(Lease$EarlyTermination) SICCode=factor(Lease$SIC.Code) Lease$TO=factor(Lease$TenantHasOption) Lease$LO=factor(Lease$LandlordHasOption) Lease$TEO=factor(Lease$TenantExercisedOption) RegA=glm(ET~1+TO, + family=binomial(link=logit), data=Lease) summary(RegA) Call: glm(formula = ET ~ 1 + TO, family = binomial(link = logit), data = Lease) Deviance Residuals: Min 1Q Median 3Q Max -0.5839 -0.5839 -0.5839 -0.3585 2.3565 Coefficients: Estimate Std. Error z value Pr(|z|) (Intercept) -1.682710.02363 -71.20 2e-16 *** TO1 -1.029590.09012 -11.43 2e-16 *** --- Signif. codes: 0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 ` ' 1 (Dispersion parameter for binomial family taken to be 1) Null deviance: 12987 on 15809 degrees of freedom Residual deviance: 12819 on 15808 degrees of freedom AIC: 12823 Number of Fisher Scoring iterations: 5 setwd(P:/Work in Progress/Haibo/Hans) Lease=read.csv(lease.csv, header=TRUE) Lease$ET - factor(Lease$EarlyTermination) SICCode=factor(Lease$SIC.Code) Lease$TO=factor(Lease$TenantHasOption) Lease$LO=factor(Lease$LandlordHasOption) Lease$TEO=factor(Lease$TenantExercisedOption) RegA=glm(ET~1+TO, + family=binomial(link=logit), data=Lease, weights=PortionSF) Warning message: non-integer #successes in a binomial glm! in: eval(expr, envir, enclos) summary(RegA) Call: glm(formula = ET ~ 1 + TO, family = binomial(link = logit), data = Lease, weights = PortionSF) Deviance Residuals: Min 1Q Median 3QMax -0.055002 -0.003434 0.00 0.00 0.120656 Coefficients: Estimate Std. Error z value Pr(|z|) (Intercept) -1.120 2.618 -0.4280.669 TO1 -1.570 9.251 -0.1700.865 (Dispersion parameter for binomial family taken to be 1) Null deviance: 1.0201 on 9302 degrees of freedom Residual deviance: 0.9787 on 9301 degrees of freedom AIC: 4 Number of Fisher Scoring iterations: 5 __ 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] calculate likelihood based on logit regression
Hi, I just ran the following logit regression. But can anyone tell me how to calculate how much more likely males (Male=1) could show such symptom than females(Male=0)? I know it must be simple to get once I have the coefficients, but I just don't recall. Thank you very much! Call: glm(formula = Symptoms ~ 1 + Male, family = binomial(link = logit), data = HA) Deviance Residuals: Min 1Q Median 3Q Max -6.038e+03 -2.067e-06 0.000e+00 0.000e+00 6.720e+03 Coefficients: Estimate Std. Errorz value Pr(|z|) (Intercept) 5.711e+00 8.466e-02 6.746e+01 2e-16 *** Male-6.493e+00 8.540e-02 -7.603e+01 2e-16 *** Best, Ed __ 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] calculate likelihood based on logit regression
I think males are z times more likely to show such symptom, where: z=(1+exp(6.493-5.711))/(1+exp(-5.711)) Is this right? Thanks! Ed. --- Haibo Huang [EMAIL PROTECTED] wrote: Hi, I just ran the following logit regression. But can anyone tell me how to calculate how much more likely males (Male=1) could show such symptom than females(Male=0)? I know it must be simple to get once I have the coefficients, but I just don't recall. Thank you very much! Call: glm(formula = Symptoms ~ 1 + Male, family = binomial(link = logit), data = HA) Deviance Residuals: Min 1Q Median 3Q Max -6.038e+03 -2.067e-06 0.000e+00 0.000e+00 6.720e+03 Coefficients: Estimate Std. Errorz value Pr(|z|) (Intercept) 5.711e+00 8.466e-02 6.746e+01 2e-16 *** Male-6.493e+00 8.540e-02 -7.603e+01 2e-16 *** Best, Ed __ 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] question regarding logit regression using glm
I got the following warning messages when I did a binomial logit regression using glm(): Warning messages: 1: Algorithm did not converge in: glm.fit(x = X, y = Y, weights = weights, start = start, etastart = etastart, 2: fitted probabilities numerically 0 or 1 occurred in: glm.fit(x = X, y = Y, weights = weights, start = start, etastart = etastart, Can some one share your thoughts on how to solve this problem? Please read the following for details. Thank you very much! Best, Ed Lease=read.csv(lease.csv, header=TRUE) Lease$ET = factor(Lease$EarlyTermination) SICCode=factor(Lease$SIC.Code) TO=factor(Lease$TenantHasOption) LO=factor(Lease$LandlordHasOption) TEO=factor(Lease$TenantExercisedOption) RegA=glm(ET~1+MSA, + family=binomial(link=logit), data=Lease, weights=Origil.SQFT) Warning messages: 1: Algorithm did not converge in: glm.fit(x = X, y = Y, weights = weights, start = start, etastart = etastart, 2: fitted probabilities numerically 0 or 1 occurred in: glm.fit(x = X, y = Y, weights = weights, start = start, etastart = etastart, summary(RegA) Call: glm(formula = ET ~ 1 + MSA, family = binomial(link = logit), data = Lease, weights = Origil.SQFT) Deviance Residuals: Min 1Q Median 3Q Max -6.038e+03 -2.066e-06 0.000e+00 0.000e+00 6.720e+03 Coefficients: Estimate Std. Errorz value Pr(|z|) (Intercept) 5.711e+00 8.466e-02 6.745e+01 2e-16 *** MSAAnchorage-6.493e+00 8.541e-02 -7.602e+01 2e-16 *** MSAAtlanta 6.894e+14 2.310e+04 2.985e+10 2e-16 *** MSAAustin -9.362e+14 4.954e+04 -1.890e+10 2e-16 *** MSABoston -2.474e+15 2.151e+04 -1.150e+11 2e-16 *** MSACharlotte-2.150e+15 7.265e+04 -2.960e+10 2e-16 *** MSAChicago -1.174e+15 2.057e+04 -5.707e+10 2e-16 *** MSACleveland-7.607e+14 7.046e+04 -1.080e+10 2e-16 *** MSAColumbus -2.768e+15 1.685e+05 -1.642e+10 2e-16 *** MSADallas2.061e+14 3.261e+04 6.321e+09 2e-16 *** MSADenver5.470e+14 3.366e+04 1.625e+10 2e-16 *** MSAEast Bay -6.191e+01 1.344e+05 -4.61e-04 1 MSAFt. Worth-6.565e+00 8.483e-02 -7.739e+01 2e-16 *** MSAHouston -2.735e+15 3.576e+04 -7.648e+10 2e-16 *** MSAIndianapolis -7.483e+14 6.588e+04 -1.136e+10 2e-16 *** MSALos Angeles -1.388e+15 2.887e+04 -4.809e+10 2e-16 *** MSAMinneapolis -1.011e+15 2.731e+04 -3.702e+10 2e-16 *** MSANashville 2.143e+01 9.395e+04 2.28e-04 1 MSANew Orleans -3.370e+15 5.038e+04 -6.689e+10 2e-16 *** MSANew York -2.526e+15 2.969e+04 -8.507e+10 2e-16 *** MSANorfolk -5.614e+01 2.020e+06 -2.78e-05 1 MSAOakland-East Bay -2.272e+15 3.642e+04 -6.239e+10 2e-16 *** MSAOrange County-5.165e+14 2.428e+04 -2.128e+10 2e-16 *** MSAOrlando -3.215e+15 1.096e+05 -2.933e+10 2e-16 *** MSAPhiladelphia -8.871e+14 4.948e+04 -1.793e+10 2e-16 *** MSAPhoenix -1.156e+01 8.807e-02 -1.313e+02 2e-16 *** MSAPortland 7.604e+14 3.841e+04 1.980e+10 2e-16 *** MSARaleigh-Durham -4.312e+01 1.294e+05 -3.33e-04 1 MSARiverside 1.626e+15 4.645e+05 3.500e+09 2e-16 *** MSASacramento -9.873e+14 5.345e+04 -1.847e+10 2e-16 *** MSASalt Lake City1.793e+15 2.029e+05 8.839e+09 2e-16 *** MSASan Antonio 9.451e+14 9.473e+04 9.977e+09 2e-16 *** MSASan Diego-3.740e+15 6.651e+04 -5.623e+10 2e-16 *** MSASan Francisco 3.109e+14 2.394e+04 1.299e+10 2e-16 *** MSASan Jose 7.392e+14 2.961e+04 2.497e+10 2e-16 *** MSASeattle -2.250e+15 1.581e+04 -1.423e+11 2e-16 *** MSASt. Louis-2.606e+15 1.801e+05 -1.447e+10 2e-16 *** MSAStamford -6.592e+00 8.469e-02 -7.784e+01 2e-16 *** MSAWashington DC 8.460e+13 3.319e+04 2.549e+09 2e-16 *** MSAWest Palm Beach -3.924e+01 2.308e+05 -1.70e-04 1 --- Signif. codes: 0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 ` ' 1 (Dispersion parameter for binomial family taken to be 1) Null deviance: 123111026 on 9302 degrees of freedom Residual deviance: 3028559052 on 9263 degrees of freedom AIC: 3028559132 Number of Fisher Scoring iterations: 25 anova(RegA) Analysis of Deviance Table Model: binomial, link: logit Response: ET Terms added sequentially (first to last) Df Deviance Resid. Df Resid. Dev NULL 9302 123111026 MSA39 0 9263 3028559052 __ 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] Convert numeric to factor
Hi, I tried to do a logistic regression with polr(MASS). I thought I already converted the response to factor, but obvious I was wrong. Could anyone tell me what I did wrong and how to correct it? Thank you very much! Lease=read.csv(LeaseDummy.csv, header=TRUE) Lease$ID - as.integer(factor(Lease$EarlyTermination)) RegA=polr(ID~1+MSA+SIC.Code+TenantOption+LLOption+TOExercised, + data=Lease, method=c(logistic)) Error in polr(ID ~ 1 + MSA + SIC.Code + TenantOption + LLOption + TOExercised, : response must be a factor summary(RegA) Best, Ed. --- Jean Eid [EMAIL PROTECTED] wrote: if labda is the elements of the vector and you know what kexp is , you can use apply apply(your_vector, 1, function(x) 1- exp^(kexp^(-x))) HTH Jean On Wed, 3 Aug 2005, Rangesh Kunnavakkam wrote: I have a large vector of around 12597 elements and I wish to calculate p-value for each element using a formula of something like: p-value= 1- exp^(kexp^(-labda)) I was wondering someone could give some ideas how to implement for each element. thankyou very much Rangesh.K __ 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] NA when using read.csv
Hi, when I used: Dist=read.csv(test.csv,header=TRUE) to read data from CSV file. For some cells, R mistakenly put in as NA, while most of the cells still appears to be right, and there is no error message in R. I am pretty sure the csv file is all right, but just can't figure out what went wrong. Can someone share your thoughts with me? Thanks! Ed __ 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] can we manage memory usage to increase speed?
Please refer to the following post. Ed --- Mike Lawrence [EMAIL PROTECTED] wrote: Date: Mon, 1 Aug 2005 00:19:06 -0300 From: Mike Lawrence [EMAIL PROTECTED] To: Briggs, Meredith M [EMAIL PROTECTED] CC: r-help@stat.math.ethz.ch Subject: Re: [R] How do you increase memeory? memory.limit(size = x) where x is the desired memory limit in MB. Quoting Briggs, Meredith M [EMAIL PROTECTED]: Hello Function memory.size() =435109888. How do I increase it by, say 30%? Thanks Meredith [[alternative HTML version deleted]] __ 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 -- Mike Lawrence, BA(Hons) Research Assistant to Dr. Gail Eskes Dalhousie University QEII Health Sciences Centre (Psychiatry) [EMAIL PROTECTED] The road to Wisdom? Well, it's plain and simple to express: Err and err and err again, but less and less and less. - Piet Hein __ 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 --- Zhilin Liu [EMAIL PROTECTED] wrote: Hi, Thanks for reading. I am running a process in R for microarray data analysis. RedHat Enterprise Linux 4, dual AMD CPU, 6G memory. However, the R process use only a total of 200M memory. And the CPU usage is total to ~110% for two. The program takes at least 2 weeks to run at the current speed. Is there some way we can increase the usage of CPUs and memories and speed up? Any suggestion is appreciated. Thanks again. Zhilin [[alternative HTML version deleted]] __ 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] logistic regression: categorical value, and multinomial
I have two questions: 1. If I want to do a binomial logit, how to handle the categorical response variable? Data for the response variables are not numerical, but text. 2. What if I want to do a multinomial logit, still with categorical response variable? The variable has 5 non-numerical response levels, I have to do it with a multinomial logit. Any input is highly appreciated! Thanks! Ed __ 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] Convert quarterly data to monthly data
Hi, I am new to use R, but can anyone tell me how to tranform quarterly data to monthly data? I know SAS has this procedure, so may I assume it is also available in R? Thanks a lot! Ed __ 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] cubic spline curves
I have a question about how to generate monthly data from quarterly data: What I want to do is basically fits cubic spline curves to the quarterly data to form continuous-time approximations of the input series, and then generate output series (monthly data) from the spline approximations. SAS can do it using proc expand: http://support.sas.com/rnd/app/examples/ets/expa/ Anyone know how to do it in R? Any input is appreciated. Best, Ed __ 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
