similar to: Testing equality of regression model on multiple groups

How would you spec a DSL which descends from Jim Weirich''s Blank Slate? I''m asking this question because I have written a DSL, and would like to have the DSL class descend from BlankSlate so that methods like == are not available in the DSL itself (in production), but only while Testing. Does any one have any insight on this? I can provide code samples if anyone would

All, Based mostly on the earlier thread on "should_be", we have introduced a new branch called should_be_working_like_ruby with the new proposed handling for equality. Per the CHANGES file in that branch (rev 896): ============================================ IMPORTANT NOTE: THIS RELEASE IS NOT 100% BACKWARDS COMPATIBLE TO 0.6.x This release changes the way RSpec handles equality.

when using the two-group discriminant analysis,we need to test for equality of covariance Matrices in lda.as whenm we formed our estimate of the within-group covariance matrix by pooling across groups,we implicitly assumed that the covariance structure was the same across groups.so it seems important the test the equality.but i can not find function in R to do these.

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

Does anybody know to introduce EQUALITY constraints in 'constrOptim' function? BR, Shubha This e-mail may contain confidential and/or privileged i...{{dropped:13}}

Dear R-mailers, I would like to test for equality of population covariance matrices. But I can't find a R tool to do so. I saw, that other people had the same question, but I could not find an answer to it, I would appreciate to know the missed link. Thank you, b.w. K. Steinmann

Hi All, I have a question about the comparison of two types. Generally, comparing two types are just comparing their pointers. However, one declared type (in programs) may be mapped into more than one llvm types, in the module resulting from linking other unit modules. For example, a class "mrViewingHitRecord" may have two corresponding IR entities:

I've started hacking up a branch with a rough implementation of equality saturation. This needs me to add objects such as PEGBasicBlock, PEGInstruction, PEGTerminatorInstruction, etc. (PEG stands for "program expression block"). I wish to share most of the infrastructure that exists - I believe this is already done with Machine*. How do I do this for PEGs? I'd also like to get

I was messing around with R and I found an example R behaving oddly: a <- alist(NULL, "bob", c(3,6,2,3)) a a == 'NULL' a == "NULL" a == 'cat' If I create a list with a NULL value >a <- alist(NULL, "bob", c(3,6,2,3)) >a [[1]] NULL [[2]] [1] "bob" [[3]] c(3, 6, 2, 3) and run some tests on 'a', the '==

Hello. I am fitting a two-level mixed model which assumes equality of variance in the lowest-level residuals across groups. The call is: fit3<-lme(CLnNAR~CLnRGR,data=meta.analysis, + na.action="na.omit",random=~1+CLnRGR|study.code) I want to test the assumption of equality of variances across groups at the lowest level. Can someone tell me how to do this? I know that one

I'm interested in doing multinomial logistic regression with equality constraints on some of the parameter values. For example, with categorical outcomes Y_1 (baseline), Y_2, and Y_3, and covariates X_1 and X_2, I might want to impose the equality constraint that \beta_{2,1} = \beta_{3,2} that is, that the effect of X_1 on the logit of Y_2 is the same as the effect of X_2 on the

Hi, I am turning to you with a (hopefully simple?) stats question. I would like to test equality of two correlation coefficients in a setting with three variables X,Y,Z, i.e. equality of r(X,Y) and r(Z,Y). I have found a formula to transform the "2 dependent correlations difference" to t-distribution with N-3 df: t = (rxy - rzy)* SQRT[{(n - 3)(1 + rxz)}/ {2(1 - rxy^2 - rxz^2 - rzy^2 +

I have conducted a discriminant function analysis with lda() in the MASS Package, and I am interested in testing that the covariance matrices of the groups are equal. Does anybody have any suggestions on how I could test for equality between covariance matrices? Any help would be great. Thank you in advance. Cheers -Rob -- [[alternative HTML version deleted]]

Hi, I tried to use the sets package yesterday, which seems to be a very powerful package: thanks to the developers. I wanted to define sets of lists where 2 lists are considered equal if they have the same length. So, I implemented: match.2.list <- function(l1,l2){ length(l1)==length(l2) } and then defined my cset as: s <- set(list(1,2),list(3,4)) lset <-

Hi all, I know that I can run an one way ANOVA on the absolute residual values to check the assumption of equal variances: model<- lm(y~x) summary(lm(abs(model$resid~x))) What if I have two factors? As far as I know I have to check this assumption on very factor/level combination. So if I have 3 factors with three levels, I would have to test 9 factor/level combinations. Here comes my

Hello, I'm writing a piece of code where I need to compare multiple same length vectors. I've gone through the basic functions like identical() or all(), but they only work for comparing 2 vectors. From 3 vectors on, it doesn't work . Example: Assuming vec1 <- c (1,2,3,4,5) vec2 <- c(1,2,3,4,5) vec3 <- c(1,2,3,4,4) identical (vec1,vec2,vec3) returns TRUE, since the 2

n=10 x1<-(1:n)/n y1<-rnorm(n,x1^2,1) m=20 x2<-(1:m)/m The value of y2 will be rnorm (m, x2^2,1) if none of the elements of x2 is same as x1, but for every same elements in x1 and x2, the value of y2 will be same as y1. I know the following is correct, but for large vectors, this won't work efficiently as this is taking longer time. Can you please let me know how to write the

is there a better way to test for equality than this user1.interests.collect(&id).sort == user2.interests.collect(&id).sort TIA GP -- Posted via http://www.ruby-forum.com/. --~--~---------~--~----~------------~-------~--~----~ You received this message because you are subscribed to the Google Groups "Ruby on Rails: Talk" group. To post to this group, send email to

Dear all, I am totally confused by the following R output, but don't have a clue for it. > a <- 1 - 0.2 > a == 0.8 [1] TRUE > a <- 1 - 0.8 > a == 0.2 [1] FALSE > a <- 1 - 0.5 > a == 0.5 [1] TRUE > a <- 1 - 0.6 > a == 0.4 [1] TRUE > a <- 1 - 0.9 > a == 0.1 [1] FALSE My R version is Windows XP R version 2.8.1 (2008-12-22).

Dear R-User, I met the problem to test equality of variance. Two sample units: conjps<-c(9.41,10.45,10.78,10.73,11.11,11.12,11.59,11.04,11.63) ms<-c(4.11,5.10,5.70,6.46,6.04,6.16, 6.24,6.32,7.33) Then I use the F test to test: •Test Equality of Two Variances F test to compare two variances data: conjps and ms F = 0.5419, num df = 8, denom df = 8, p-value = 0.4045 alternative