search for: sumry

I wrote a function which does "moving window" regressions. E.g. if there are 100 observations and the window width is 50, then I first run the regression for observations 1..50, then for 2..51, and so on. I am extremely pleased with R in my experience with writing this, since I was able to pass the model as an argument into the function :-) Forgive me if I sound naive, but that's

...ght. labelPos <- ifelse(datsummNT$mean - mean(datsummNT$mean, na.rm=T) > 0, 2, 4) text(datsummNT$mean, datsummNT$var, labels=rownames(datsummNT), cex=0.8, pos=labelPos) x <- data.frame(x=rnorm(100), y = gl(50,2), z = rep(1:4, 25), ab = gl(2,50)) summarize(x) summarize(x, numLevels=15) sumry <- summarize(x) sumry[[1]] ##another way to get the numerics output sumry[[2]] ##another way to get the factors output dat <- data.frame(x=rnorm(100), y = gl(50,2), z = factor(rep(1:4, 25), labels=c("A","B","C","D")), animal=factor(ifelse(runif(100)&lt...

...45 high 15 medium 44 > ------------------ function test.terms and functions it calls ------------------------ > test.terms function (object, ...) { UseMethod("test.terms") } > test.terms.lm function (mod, error, ...) { if (!missing(error)) { sumry <- summary(error, corr = FALSE) s2 <- sumry$sigma^2 error.df <- error$df.residual error.SS <- s2 * error.df } intercept <- has.intercept(mod) p <- length(coefficients(mod)) I.p <- diag(p) Source <- term.names(mod) n.terms <-...

...3.3> [1] T My change to summary.default was to fix the following warning in Splus3.2 and 3.3: > summary.default(list(z, a=list(1:3))) Length Class Mode 3 a numeric a 1 list Warning messages: Replacement length not a multiple of number of elements to replace in: sumry[ i, 2] <- class(ii) and consisted simply of changing sumry[i, 2] <- if (is.object(ii)) class(ii) to sumry[i, 2] <- if (is.object(ii)) paste(class(ii), collapse=" ") This may not be necessary in the current R version, but because of the above error...

Hello sir: Here's the result of repeated measures ANOVA. $"Error: Within" Df Sum Sq Mean Sq F value Pr(>F) t 2 524177 262089 258.24 1.514e-06 *** Residuals 6 6089 1015 --- Signif. codes: 0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 ` ' 1 My question is: How to extract the F value only? If the result is a

...lm( formula(fmla), data=dat) results[[ i ]] <- maux print(maux$call[2]) ###fix me fix me ## } results } mcDiagnose <- function(model){ auxRegs <- lmAuxiliary(model) auxRsq <- numeric(length=length(auxRegs)) j <- 0 for ( i in auxRegs ){ j <- j + 1 sumry <- summary(i) auxRsq[j] <- sumry$r.squared } print("Drum roll please!") print("And your R_j Squareds are (auxiliary Rsq)") print(names(auxRegs)) print(auxRsq) } x1 <- rnorm(100) x2 <- rnorm(100) y <- rnorm(100) m1 <- lm(y~x1+x2) mcDiagnose(m1)...

...9;m trying to use the library mclust for gaussian mixture on a numeric vector. The function Mclust(data,G=3) is working fine but the fitting is not optimal and is using modelNames="E". When I'm trying Mclust(data,G=3,modelName="V") I have the following message: Error in if (Sumry$G > 1) ans[c(orderedNames, "z")] else ans[orderedNames] : argument is of length zero In addition: Warning message: In pickBIC(object[as.character(G), modelNames, drop = FALSE], k = 3) : none of the selected models could be fitted Using variable variance would fit my data better,...

...9;m trying to use the library mclust for gaussian mixture on a numeric vector. The function Mclust(data,G=3) is working fine but the fitting is not optimal and is using modelNames="E". When I'm trying Mclust(data,G=3,modelName="V") I have the following message: Error in if (Sumry$G > 1) ans[c(orderedNames, "z")] else ans[orderedNames] : argument is of length zero In addition: Warning message: In pickBIC(object[as.character(G), modelNames, drop = FALSE], k = 3) : none of the selected models could be fitted Using variable variance would fit my data better,...

...3 13.9171 6.495e-05 *** Residuals 11 8254 750 According to the unbalanced design, I requested the type III SS which resulted in an error statement library(car) Anova(example.lm, type="III") Error in linear.hypothesis.lm(mod, hyp.matrix, summary.model = sumry, : One or more terms aliased in model. by using glm I got results with 0 df for the sequence effect !!!! example.glm<-glm(outcome~treatment+period+sequence+subject%in%sequence, data=example, family=gaussian) library(car) Anova(example.glm,type="III",test.statistic="F...

...31 74110911 2390675 I have tried using both the drop1() command and the Anova() command in the car package. When I use the Anova command I get the following error message: >Anova(carbonmean,type="III") “Error in linear.hypothesis.lm(mod, hyp.matrix, summary.model = sumry,: One or more terms aliased in model.” I am not sure why this is aliased. There are no missing cells, and the cells are balanced (aside from for the covariate). Each Phyto by Zoop cross is replicated 3 times, and there are four Phyto levels within each level of Diversity. When I remove the neste...

...ls 31 74110911 2390675 I have tried using both the drop1() command and the Anova() command in the car package. When I use the Anova command I get the following error message: >Anova(carbonmean,type="III") ?Error in linear.hypothesis.lm(mod, hyp.matrix, summary.model = sumry,: One or more terms aliased in model.? I am not sure why this is aliased. There are no missing cells, and the cells are balanced (aside from for the covariate). Each Phyto by Zoop cross is replicated 3 times, and there are four Phyto levels within each level of Diversity. When I remove the nested...

...<- function(model, type=c("hc3", "hc0", "hc1", "hc2", > "hc4"), > > ...){ > if (!require(car)) stop("Required car package is missing.") > type <- match.arg(type) > V <- hccm(model, type=type) > sumry <- summary(model) > table <- coef(sumry) > table[,2] <- sqrt(diag(V)) > table[,3] <- table[,1]/table[,2] > table[,4] <- 2*pt(abs(table[,3]), df.residual(model), lower.tail=FALSE) > sumry$coefficients <- table > p <- nrow(table) > hyp &l...