similar to: Mimicking SPSS weighted least squares

Hi all, 1. I am doing some data analysis using both R and SPSS, to get used to both software packages. I had performed linear regression in R and SPSS for a number of times before this last one and the resulting coefficient values always matched. However, this last data set I was analyzing using simple linear regression and using the command lm(y~x), gave me different readings from R and

Hello, I have a data set of data which is best fit by an exponential decay function. I would like to use a nonlinear weighted least squares regression. What function should I be using? Thank you! [[alternative HTML version deleted]]

Dear All, Which package/function could i use to solve following linear least square problem? A over determined system of linear equations is given. The nnls-function may would be a possibility BUT: The solving is constrained with a inequality that all unknowns are >= 0 and a equality that the sum of all unknowns is 1 The influence of the equations according to the solving process is

Hello, is it possible in R to calculate a Weighted averaging partial least squares regression? I'm not firm in statistics and didn't found anything about weighted averaging in combination with PLS in the help archives. Or is it possible to develop a workaround with the pls-package? thanks for help in advance Andreas Plank -- _____________________________________________ Dipl. Biol.

Dear all, I encounter some discrepancies when comparing the deviance of a weighted and unweigthed model with the AIC values. A general example (from 'nls'): DNase1 <- subset(DNase, Run == 1) fm1DNase1 <- nls(density ~ SSlogis(log(conc), Asym, xmid, scal), DNase1) This is the unweighted fit, in the code of 'nls' one can see that 'nls' generates a vector

I need to find out the difference between the way R calculates weighted regression and standard regression. I want to plot a 95% confidence interval around an estimte i got from least squares regression. I cant find he documentation for this ive looked in ?stats ?lm ?predict.lm ?weights ?residuals.lm Can anyone shed light? thanks Chris. -- View this message in context:

Hi everyone, I admit I am a bit of an R novice, and I was hoping someone could help me with this error message: Warning message: In lm.fit(x, y, offset = offset, singular.ok = singular.ok, ...) : extra arguments weigths are just disregarded. My equation is: lm( Y ~ X1 + X2 + X3, weigths = seq(0.1, 1, by = 0.1)) -- View this message in context:

I got simple x,y pairs of data and simple scatterplot and just cannot figure how to do it , there are many examples but always there is error popping out please show me an example stripped with additional data just core of what I need to do to get this damn line -- View this message in context:

As John noted, there are different kinds of weights, and different terminology: * inverse-variance weights (accuracy weights) * case weights (frequencies, counts) * sampling weights (selection probability weights) I'll add: * inverse-variance weights, where var(y for observation) = 1/weight (as opposed to just being inversely proportional to the weight) * weights used as part of an

Hi, I am using R to do a principal components analysis for a class which is generally using SPSS - so some of my question relates to SPSS output (and this might not be the right place). I have scoured the mailing list and the web but can't get a feel for this. It is annoying because they will be marking to the SPSS output. Basically I'm getting different values for the component

Howdy! I'm a clinical psychologist desperately trying to get rid of SPSS. I just discovered R and like it quite a lot. The main reason why we're still using SPSS is the hierarchical regression where you enter bundles of variables into a linear model and get an R-sqare increase tested with an F-test. I already found add1 and drop1 but would rather need addn and dropn. Is there

Hi there, I'm trying to fit a growth curve to some data and need to use a weighted least squares estimator to account for heteroscedasticity in the data. A weights argument is available in nls that would appear to be appropriate for this purpose, but it is listed as 'not yet implemented'. Is there another package which could implement this procedure? Regards, Robert Brown

Hello, I believe the aov() function in R uses a "Type-I sum-of-squares" by default as against "Type-III". This is relevant for me because I am trying to understand ANOVA in R using my knowledge of ANOVA in SPSS. I can only reproduce the results of an ANOVA done using R through SPSS if I specify that SPSS uses a Type-I sum-of-squares. (And yes, I know that when the sample

Greetings. I'm trying to replicate an analysis I did a few years ago, then in SPSS, using the SPSS GLM command: GLM n_diffpt WITH age_i inc_i join_i work_i educ_i give_i cs_i eff_i age_a inc_a join_a work_a educ_a give_a cs_a eff_a /METHOD = SSTYPE(3) /INTERCEPT = INCLUDE /PRINT = PARAMETER ETASQ RSSCP GEF /CRITERIA = ALPHA(.05) /DESIGN = age_i*age_a inc_i*inc_a

SPSS seems to have changed its default datafile format, resulting in issues for read.spss(). In Windows this results in a warning, in Debian the import completely fails: Debian (R version 2.8.0 (2008-10-20) i486-pc-linux-gnu, foreign_0.8-29) > read.spss("/home/jeroen/samples/Tomato.sav") Error in iconv(names(rval), cp, "") : unsupported conversion from 'CP65001'

Hi all, I met with a problem about the weighted least square regression. 1. I simulated a Normal vector (sim1) with mean 425906 and standard deviation 40000. 2. I simulated a second Normal vector with conditional mean b1*sim1, where b1 is just a number I specified, and variance proportional to sim1. Precisely, the standard deviation is sqrt(sim1)*50. 3. Then I run a WLS regression without the

Hello, does anyone have experience with reading SPSS Version 15.0 files into R (version 2.4.1, WinXP)? I have long been sucessfully reading SPSS files with read.spss from the wonderful foreign package, but somehow after upgrading from SPSS14 to SPSS15 I seem to have problems. Trying a simple example, where test.sav is a SPSS 15.0 data file consisting of x1=c(1,2,3) and

Hi all. I have an SPSS file that I'm loading into R with the Hmisc spss.get function. The trouble is that the SPSS file uses the Windows-1252 character set (which I think is the default for SPSS on Windows) instead of plain-ol' Latin-1, and since spss.get doesn't allow me to pass the "reencode" option to read.spss, any characters in Windows-1252 that are not a part of Latin-1

Full_Name: Roger Newton Version: 2.8.1 OS: windows 2000 Submission from: (NULL) (80.176.228.157) I have an elderly version of SPSS (version 11) which I still use. R Version 2.6.1 would, and still will, read SPSS *.sav files produced by SPSS version 11. R version 2.8.1 which I installed two days ago (05/02/09) reports an error and shuts down when trying to read SPSS version 11 *.sav files using

I am using spss.get to import an SPSS database "Data.sav", created with SPSS 14 : df1 <- spss.get("C:/temp/Data.sav" , lowernames=TRUE, datevars = c("dateinte")) I am getting this warning. I get the same warning with read.spss. Warning message: C:/temp/Data.sav: Unrecognized record type 7, subtype 16 encountered in system file This is a stupid