search for: cv1

Dear all Sorry for simple question: I want to put the following option into look as number of X is large 1000 variables X1 <- sample(c(1,2, 3, 4),10, replace = T, prob = c(0.4, 0.2, 0.2, 0.2)) cv1 <- round(runif(2, 1, 10)) # X2 is copy of X1 X2 <- X1 # now X2 is different in cv1 random positions X2[cv1] <- 5 cv2 <- round(runif(2, 1, 10)) # X3 is copy of X2 X3 <- X2 X3[cv2] <- 5 …. So on till X10 mydf <- data.frame ( X1, X2, X3, X4, X5, X6, X7, X8, X9, X1...

...1, 'V3 <-> V3','e3', 1, 'V4 <-> V4','e4', 1, 'V5 <-> V5','e5', 1, 'F1 <-> F1','d1', 1, 'F2 <-> F2','d2', 1, 'F1 <-> F2','c12',NA, 'V1 <-> V2','cv1', NA, ),ncol=3,byrow=T) obs.vars.mh <- c('V1','V2','V3','V4','V5') rownames(data.mh) <- colnames(data.mh) <- obs.vars.mh sem.mh <- sem(model.mh, data.mh, 100) ### At this stage, everything looks going well. By debug mode of "sem()"...

...ut I am less familiar with R, so I was hoping someone could offer some suggestions. Oddly simple ANOVA is the same in SPSS and R. Including covariates improves the main effect (p-value) in R and diminishes it in SPSS.. The formula I have been using is: >Y = cbind(dV1, dV2, dV3) >aov(lm(Y~iV1+cV1+cV2)) The main?independent?variable is disease group and the covariates are continuous nuisance variables such as age. Both nuisance variables interact with the dependent variable but not each other. The frequency distribution of the covariates is similar for each group, but the groups are not mat...

Dear list, We have encountered problems with the package mvbutils while creating (or reading from disk) timeSeries objects. Below is a very simple example of the problem. We are using R 2.12 in  a PC running Windows 7  64-bit Professional. ----------- library(timeSeries)   cv1 <- as.character(as.Date(1:10, origin = "1970-01-01")) ts1 = timeSeries(1:10, cv1, units = NULL)   print(ts1)   library(mvbutils)   ts2 = timeSeries(1:10, cv1, units = NULL)   print(ts2) print(ts1) # Both objects have problems --------------   This is the error message generated when pr...

...s, 1-sum(variable.cnts.prs)) tst                    <-     chisq.test(variable.cnts, p=variable.cnts.prs)   chi_squared        <-     as.numeric(unclass(tst)$statistic) p_value             <-     as.numeric(unclass(tst)$p.value) df                     <-     tst[2]$parameter     cv1                    <-     qchisq(p=.01, df=tst[2]$parameter, lower.tail = FALSE, log.p = FALSE)   cv2                    <-     qchisq(p=.05, df=tst[2]$parameter, lower.tail = FALSE, log.p = FALSE)   cv3                    <-     qchisq(p=.1, df=tst[2]$parameter, lower.tail = FALSE, lo...

...s, 1-sum(variable.cnts.prs)) tst ?????????????????? <-???? chisq.test(variable.cnts, p=variable.cnts.prs) ? chi_squared ?????? <-???? as.numeric(unclass(tst)$statistic) p_value? ?????????? <-???? as.numeric(unclass(tst)$p.value) df ??????????????????? <-???? tst[2]$parameter ? ? cv1??????????????????? <-???? qchisq(p=.01, df=tst[2]$parameter, lower.tail = FALSE, log.p = FALSE) ? cv2??????????????????? <-???? qchisq(p=.05, df=tst[2]$parameter, lower.tail = FALSE, log.p = FALSE) ? cv3??????????????????? <-???? qchisq(p=.1, df=tst[2]$parameter, lower.tail = FALSE, lo...

...s, 1-sum(variable.cnts.prs)) tst                    <-     chisq.test(variable.cnts, p=variable.cnts.prs)   chi_squared        <-     as.numeric(unclass(tst)$statistic) p_value             <-     as.numeric(unclass(tst)$p.value) df                     <-     tst[2]$parameter     cv1                    <-     qchisq(p=.01, df=tst[2]$parameter, lower.tail = FALSE, log.p = FALSE)   cv2                    <-     qchisq(p=.05, df=tst[2]$parameter, lower.tail = FALSE, log.p = FALSE)   cv3                    <-     qchisq(p=.1, df=tst[2]$parameter, lower.tail = FALSE, lo...

...riable.cnts.prs)) tst ?????????????????? <-???? chisq.test(variable.cnts, p=variable.cnts.prs) ? chi_squared ?????? <-???? as.numeric(unclass(tst)$statistic) p_value? ?????????? <-???? as.numeric(unclass(tst)$p.value) df ??????????????????? <-???? tst[2]$parameter ? ? cv1??????????????????? <-???? qchisq(p=.01, df=tst[2]$parameter, lower.tail = FALSE, log.p = FALSE) ? cv2??????????????????? <-???? qchisq(p=.05, df=tst[2]$parameter, lower.tail = FALSE, log.p = FALSE) ? cv3??????????????????? <-???? qchisq(p=.1, df=tst[2]$parameter, lower.tail = FAL...

...quot;RF", denoted in the model by weights=vf3. The model is: > lmeF2 <- lme(CV ~ Depth * RF * Season/Period, random = ~ 1 | Pop/Ind, > method = "REML", data = trf, weights=vf3) > Anova(lmeF2, type="III") Analysis of Deviance Table (Type III tests) Response: CV1 Chisq Df Pr(>Chisq) (Intercept) 2.7866 1 0.0950585 . Depth 24.0113 2 6.110e-06 *** RF 23.3307 1 1.364e-06 *** Season 1.4841 1 0.2231326 Depth:RF 73.0870 2 < 2.2e-...

...omb ## input: vec -- vector ## output: all possible combination from the elements of vec #################### rec.comb=function(vec) { if(length(vec)==0){list(NULL) }else { tmp=rec.comb(vec[-1]) tmp2=sapply(tmp,function(x)c(vec[1],x)) c(tmp,tmp2) } } #################### ## function: CV1glm--CV1 using K fold CV ## input: y -- response vector; x -- predictors without intercept ## output: the vector whether each predictor should be selected. E.g. (0,1,0,1) means no intecept while var1 and var3 should be selected #################### CV1glm=function(y,x){ n.var=ncol(x) n=nrow(x) c...

...ruction that fuses I with J. > + Value *BBVectorize::getReplacementInput(LLVMContext& Context, Instruction *I, > + Instruction *J, unsigned o, bool FlipMemInputs) { Indentation. > + Value *CV0 = ConstantInt::get(Type::getInt32Ty(Context), 0); > + Value *CV1 = ConstantInt::get(Type::getInt32Ty(Context), 1); > + > + // Compute the fused vector type for this operand > + Type *ArgType = I->getOperand(o)->getType(); > + VectorType *VArgType = getVecType(ArgType); > + > + Instruction *L = I, *H = J; > + if (FlipMe...

...nt type. When a prvalue v of object pointer type is > converted to the object pointer type “pointer to cv T”, the result > is static_cast<cv T*>(static_cast<cv void*>(v)). > > C++ [expr.static.cast]p13 says of conversions from void*: > A prvalue of type “pointer to cv1 void” can be converted to a > prvalue of type “pointer to cv2 T” .... If the original pointer value > represents the address A of a byte in memory and A satisfies the alignment > requirement of T, then the resulting pointer value represents the same > address as the original poi...

...gt; + Value *BBVectorize::getReplacementInput(LLVMContext& Context, Instruction *I, > > + Instruction *J, unsigned o, bool FlipMemInputs) { > > Indentation. > > > + Value *CV0 = ConstantInt::get(Type::getInt32Ty(Context), 0); > > + Value *CV1 = ConstantInt::get(Type::getInt32Ty(Context), 1); > > + > > + // Compute the fused vector type for this operand > > + Type *ArgType = I->getOperand(o)->getType(); > > + VectorType *VArgType = getVecType(ArgType); > > + > > + Instruction *L = I...

On Mon, 2011-11-21 at 21:22 -0600, Hal Finkel wrote: > On Mon, 2011-11-21 at 11:55 -0600, Hal Finkel wrote: > > Tobias, > > > > I've attached an updated patch. It contains a few bug fixes and many > > (refactoring and coding-convention) changes inspired by your comments. > > > > I'm currently trying to fix the bug responsible for causing a compile

...ct pointer of a different type. When a prvalue v of object pointer type is converted to the object pointer type “pointer to cv T”, the result is static_cast<cv T*>(static_cast<cv void*>(v)). C++ [expr.static.cast]p13 says of conversions from void*: A prvalue of type “pointer to cv1 void” can be converted to a prvalue of type “pointer to cv2 T” .... If the original pointer value represents the address A of a byte in memory and A satisfies the alignment requirement of T, then the resulting pointer value represents the same address as the original pointer value, that is,...

...gt; + Value *BBVectorize::getReplacementInput(LLVMContext& Context, Instruction *I, > > + Instruction *J, unsigned o, bool FlipMemInputs) { > > Indentation. > > > + Value *CV0 = ConstantInt::get(Type::getInt32Ty(Context), 0); > > + Value *CV1 = ConstantInt::get(Type::getInt32Ty(Context), 1); > > + > > + // Compute the fused vector type for this operand > > + Type *ArgType = I->getOperand(o)->getType(); > > + VectorType *VArgType = getVecType(ArgType); > > + > > + Instruction *L = I...

On Mon, 2011-11-21 at 11:55 -0600, Hal Finkel wrote: > Tobias, > > I've attached an updated patch. It contains a few bug fixes and many > (refactoring and coding-convention) changes inspired by your comments. > > I'm currently trying to fix the bug responsible for causing a compile > failure when compiling >