similar to: Error: system is computationally singular: reciprocal condition number

Hi All, This is my R-version information:--- > version _ platform i486-pc-linux-gnu arch i486 os linux-gnu system i486, linux-gnu status major 2 minor 7.1 year 2008 month 06 day 23 svn rev 45970 language R version.string R version 2.7.1 (2008-06-23) While calculating partial

Why do we get Partial correlation values greater than 1? I have used the default function pcor.mat :-- I have manipulated the default pcor.mat function a bit so ignore tha variables corr_type,element1_in_no,element2_in_no,P.Please ignore the ?pairwise? section and have a look at athe ?listwise ? part i.e else part. *pcor.mat <-

Dear friends i am trying to fit an Ornstein-Uhlenbeck process by MAXIMUM LIKELYHOOD method. i found these formulas on http://www.sitmo.com/article/calibrating-the-ornstein-uhlenbeck-model/ this is the mean-reverting process http://r.789695.n4.nabble.com/file/n4637271/process.txt process.txt and this is the script that i am using....... ouFit.ML=function(spread) { n=length(spread)

Dear Mac users, Hi, as you might have probably read the thread of "[R] Rsquared in summary(lm)" on May 10, it seems that Mac version of lm() seem to be working incorrectly. I enclose the script to produce the result both for lm() and manual calculation for a simple regression. Could you run the script and report with the version of R, so I don't have to go through every builds

Hi I just upgraded to http://svn.xiph.org/trunk/speex r10357 and got this build warning: alfredh@io:$ make -s mdf.o libspeex/mdf.c: In function 'speex_echo_cancel': libspeex/mdf.c:321: warning: statement with no effect libspeex/mdf.c:317: warning: `adapt_rate' might be used uninitialized in this function Is this intentional? In any case here is a simple fix: Index:

Below is a version of [.data.frame that is faster for subscripting rows of large data frames; it avoids calling duplicated(rows) if there is no need to check for duplicate row names, when: i is logical attr(x, "dup.row.names") is not NULL (S+ compatibility) i is numeric and negative i is strictly increasing "[.data.frame" <- function (x, i, j,

Hi, I'm having problems while working with large data sets with R 1.5.1 in windows 2000. Given a integer matrix size of 30 columns and 15000 rows my function should return a boolean matrix size of about 5000 rows and 15000 columns. First of all I tried to run this function on computer with 256 MB of RAM. I increased memory limit of R with memory.limit() up to 512 MB. I was inspecting

Hello, I wanted to set my own time intervals for shutdown. {poweroff,return,paused.return}, so I had to change sources, where it has been set in a hard way. poweroff: Sxx\r return: Zxx\r paused.return: SxxRyyyy\r Solution A: Why not adding an info about these commands in a generic way and issuing shutdown.{poweroff.xx,return.xx,paused.return.xxyyyy} Solution B: Why not creating a special

hi, am trying to understand speex's algo. have a few questions. 1) autocorrelation: in the function, _spx_autocorr (for floating point version), there is a line ac[0] += 10; correct me if i am wrong, i suppose the addition of 10 is used to condition the autocorrelation matrix. wonder how the value of 10 is arrived at? 2) levinson durbin (LD) algo in the function _spx_lpc, i referred

Hi, the function makeARIMA(), designed to construct some state space representation of an ARIMA model, uses a C function called getQ0, which can be found at the end of arima.c in R source files (library stats). getQ0 takes two arguments, phi and theta, and returns the covariance matrix of the state prediction error at time zero. The reference for getQ0 (cited by help(arima)) is:

Full_Name: Marek Ancukiewicz Version: 2.01 OS: Linux Submission from: (NULL) (132.183.12.87) It seems that the the standard error of prediction of the linear regression, caclulated with predict.lm is incorrect. Consider the following example where the standard error is first calculated with predict.lm, then using delta method. and finally, using the formula rms*sqrt(1+1/n+(xp-x0)^2/Sxx). Marek

Hello, I'm doing some linear regression: >lm<-lm(osas~alp,data) >summary(lm) However, the Rsquared in the output of summary() is not the same as the "standard" Rsquared calculated by spreadsheets, and outlined in statistical guidebooks, being SSR/SSTO. The output says "multiple Rsquared", but it is no multiple regression... What's the difference? Thanks,

I have a set of data in the form x1, y1, z1 x1, y2, z2 ... x1, yN, zN x2, y1, z(N+1) x2, y2, z(N+2) ... x2, yN, z(2N) ...and so on... xM, yN, val(M*N) I have been trying to figure out how to get R to use this data in a persp plot. So far the only thing that I can figure out to do is to break the data file into three different files. The first file contains the x-coordinate data: x1 x2

Hello- I upgraded Samba from 4.6 to 4.8 on a FreeBSD 11.2 server. After the upgrade, users cannot access the HOME folder share but they can access other shares just fine. I am using the RID backend on this member server that connects to Windows-based domain controllers. I apologize for the lengthy smb4.conf but here it is: #======================= Global Settings

Hi friends, I have a query regarding na.omit function.Please ,someone help me. I have a function xyz_function<-function(arguments) { some code return(list(matrix=dataset)) } xyz_function_returnvalue<-xyz_function(passed argumentss) *Case-I* xyz_function_returnvalue_deletingNArows<-na.omit((xyz_function_returnvalue)) *Case-II*

Hi, anybody have any ideas on this ? I have two sequences of proportions. Due to conventions in my field, I need to produce a linear correlation between the two. Each sequence of proportions are based upon differing numbers of observations (although within a sequence the number of observations may not fluctuate too much) so it may be necessary/advisable to variance stabilize. Is their a best

Hi all, Can anyone suggest me how to insert rows in between data frames and also keep the ordering of row numbers correct? Estimate Std. Error t value Pr(>|t|) recmeanC2 9.275880e-17 6.322780e-17 1.467057e+00 0.14349903 recmeanC3 1.283534e-17 2.080644e-17 6.168929e-01 0.53781390

Hi friends, Please can anyone help me with an easier solution of doing the below mentioned work. Suppose i have a dataset like this:--- i1 i2 i3 i4 i5 1 7 13 1 2 2 8 14 2 2 3 9 15 3 3 4 10 16 4 4 5 11 17 5 5 6 12 18 6 7 *i1,i2,i3,i4,i5 are my items.I am able to find all possible pairs i.e Say this dataframe is "item_pairs" **i1,i2 **i1,i3 **i1,i4 i1,i5 **i2,i1

---------- Forwarded message ---------- From: Moumita Das <das.moumita.online@gmail.com> Date: Sat, May 16, 2009 at 2:26 PM Subject: Cannot allocate a new database connection error To: r-help-request@r-project.org Hi friends, why do i keep getting this error?The program runs, twice and every third time i get this error.I have to quit.Again get teh R-prompt and then run the script. *Error

Hi All , Can anybody tell me if there's any way to get the summarized anova values.Now i will explain what i mean , when i say "*summarized*". Below you can see the anova table of recmeanC1 with rest* all* i.e from recmeanC2 to i15(predictors),as shown in table. Df Sum Squares Mean Square F value Significance [Pr(>F)] recmeanC2 1 89.272 89.272