similar to: How to write out this regression equation in R?

My stepAIC function works for one set of data but not another....one set of data shows the steps of eliminating variables, versus another set of data doesn't throw away any variables. Can anyone please explain why? Thanks ______________________________________________________________________ The information transmitted, including any attachments, is intended only for the person or entity

See error message below: can someone please help with this? Thanks! Residuals: ALL 9 residuals are 0: no residual degrees of freedom! Residual standard error: NaN on 0 degrees of freedom Multiple R-squared: 1, Adjusted R-squared: NaN F-statistic: NaN on 8 and 0 DF, p-value: NA ______________________________________________________________________ The information transmitted,

Can someone please help with the below - thanks! Warning messages: 1: Not plotting observations with leverage one: 7 2: Not plotting observations with leverage one: 7 > print(qqPlot(fit),envelop=.95); Error in model.frame.default(formula = Y ~ X - 1, drop.unused.levels = TRUE) : variable lengths differ (found for 'X') In addition: Warning message: In matrix(yhat, n, reps) : data

Can someone please help with the error message below? thanks! Start: AIC=-Inf value ~ 1 + Core_CPI__ + GDP_change + Unemployment + housing + interest + S_P + d1 + d2 + d3 Error in if (any(ch)) { : missing value where TRUE/FALSE needed In addition: Warning message: attempting model selection on an essentially perfect fit is nonsense

Can someone please help with the error message below? Warning messages: 1: Not plotting observations with leverage one: 7 2: Not plotting observations with leverage one: 7 > print(qqPlot(fit),envelop=.95); Error in model.frame.default(formula = Y ~ X - 1, drop.unused.levels = TRUE) : variable lengths differ (found for 'X') In addition: Warning message: In matrix(yhat, n, reps) :

Ran a bunch of variables in R and the final result of StepAIC is as below: Why are the first 5 variables kept in the stepwise result?? Are the last 4 variables finally chosen after Stepwise? Thanks Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 1.315e-01 2.687e-01 0.490 0.63611 Core_CPI__ 1.290e-02 7.496e-03 1.721 0.11927 GDP_change -3.482e-03 2.075e-03 -1.678 0.12767

For a set of data showing seasonality (related to the 4th quarter), ncv test in R shows p-value of 0.008 which rejects the null hypothesis of constant-variance. How to apply White's standard error in R? thanks ______________________________________________________________________ The information transmitted, including any attachments, is intended only for the person or entity to

Can someone please help with the error message below -- thanks! Warning messages: 1: Not plotting observations with leverage one: 7 2: Not plotting observations with leverage one: 7 > print(qqPlot(fit),envelop=.95); Error in model.frame.default(formula = Y ~ X - 1, drop.unused.levels = TRUE) : variable lengths differ (found for 'X') In addition: Warning message: In matrix(yhat, n,

For example, if coefficient's p-value is less than 0.1 I want the stepwise to automatically drop that variable. Can the stepAIC be customized to do that? SAS seems to be able to customized stepwise function with p-value or cooks'd. thanks! ______________________________________________________________________ The information transmitted, including any attachments, is intended only

For a set of data showing seasonality (related to the 4th quarter), ncv test shows p-value of 0.008 which rejects the null hypothesis of constant-variance. Currently a linear LM relationship is being applied to the data. Should white's error be used to correct the non-constant variance? Are the p-values of the coefficients unreliable? thanks

fit lwr upr 1 218.4332 90.51019 346.3561 2 218.3906 90.46133 346.3198 3 218.3906 90.46133 346.3198 4 161.3982 44.85702 277.9394 5 192.4450 68.39903 316.4909 6 179.8056 56.49540 303.1158 7 219.5406 91.52707 347.5542 8 162.6761 46.65760 278.6945 9 193.8506 70.59838 317.1029 10 181.3816 58.11305 304.6502 11 221.2871 92.14366 350.4305 12 164.2947 47.91081 280.6785 13

What is the "classic" R function for solving a (possibly over determined) system of non-linear equations? Thank you! Moshe Olshansky e-mail: moshe.olshansky@brevanhoward.com The information transmitted is intended only for the person(s) or entity to which it is addressed and may contain confidential and/or privileged material. Any review, retransmission, dissemination or

Dear All, I would like to fit some parametric survival models using left truncated, right censored data in R. However I am having problems finding a function to fit parametric survival models which can handle left truncated data. I have tested both the survreg function in package survival: fit1 <- survreg(Surv(start, stop, status) ~ X + Y + Z, data=data1) and the psm function in package

Dear R community, I'm trying to graphically illustrate my data with a worlmap. Unfortunately, my data is partly on country basis and partly on regional basis (e.g. certain African countries are aggregated to one region). I am using the package rwoldmap. The data on country basis can be mapped, but our defined regions cannot be identified in R. Therefore, all the countries in these

Dear All, We are currently working with very large datasets which even in R require a lot of calculation time. Is there an option of including a function/ tool or something alike which shows the remaining time of calculation? Just to see whether there is any progress or whether anything has crashed and to get a feeling whether we have to wait for 5 min or 30min... Any help is greatly

Dear All, at the moment I am using R for calculations of large databases. Unfortunately, R only manages to complete certain operations at some times, and not at others. I usually get the error message "cannot allocate vector of size XX" I am using the 64-bit version with Windows 7. While my computer has 8 RAM, I do have a feeling that R cannot use all of it. Searching online, I

Hello, i used rsync for some years ago...Well fine because i synchronize laptops and servers or laptops and PCs using rsync AND between both unix/linux machines and unix/linux filesystems. Ok. Now, i have to synchronize files that are on unix/linux filestems AND on win filesystems (NTFS and FAT)...I thought: "don't worry, mounting win filsystems with samba and so on". Yes

Hi, tryCatch seems to be evaluating the all expressions wrapped in it before passing control to the error handling function. For example, the code below will try to evaluate "results" even though the call to odbcConnect fails. I was hoping that the mechanism would work in the same way as a C++ try catch structure and pass control to the catch... as soon as an exception is generated.

Dear Tomas, thank you for looking into this. Here's the output: # number of logical processors - what detectCores() should return out <- system("wmic cpu get numberoflogicalprocessors", intern=TRUE) [1] "NumberOfLogicalProcessors \r" "22 \r" "22 \r" [4] "20 \r"

Hi. I need to apply run a regression analysis for groups of data of fixed length:100 As, 100 Bs, 100 Cs etc. eg x Key Value A 1 A 21.2 A 4 A 6.5 ...repeat 96 times with differing values of A B 1 B 2.3 B NA B 6.5 ...repeat 96 times with differing values of B etc I run these against a linear model using tapply(data$Value, data$Key,FUN=regr,100)