search for: rsquared

Hey I'm not really sure what I should put on here, but I am having trouble with my R code. I am trying to get the p-values, R^2s etc for a number of different groups of variables that are all in one dataset. This is the code: #Stand counter st<-1 #Collections stands<-numeric(67) slopes<-numeric(67) intercepts<-numeric(67) mses<-numeric(67) rsquares<-numeric(67)

I estimate two competing simple regression models, A and B where the LHS is the same in both cases but the predictor is different ( I handle the intercept issue based on other postings I have seen ). I estimate the two models on a weekly basis over 24 weeks. So, I end up with 24 RSquaredAs and 24 RsquaredBs, so essentally 2 time series of Rsquareds. This doesn't have to be necessarily thought of as a time series problem but, is there a usual way, given the Rsquared data, to test H0 : Rsquared B = Rsquared A versus H1 : Rsquared B > Rsquared A so that I can map the 24 R s...

Hi, I'm using glm function to do logistic regression and now I want to know if it exists a kind of R-squared with this function in order to check the model. Thank you.

Hi, I have something like this: > x <- 1:10 > y2 <- 30+5*x+rnorm(x,sd=3) > y <- c(y1,y2) > x <- c(x,x) > plot(x,y) > x <- 1:10 > y1 <- 1+5*x+rnorm(x,sd=2) > y2 <- 30+5*x+rnorm(x,sd=5) > y <- c(y1,y2) > x <- c(x,x) > f <- factor(rep(c("a","b"),c(10,10))) > m <- lm(y~x+f) > anova(m) Analysis of Variance

Dear all, I have a question regarding the output of the coxph function. What does the 'max possible' exactly mean in the output below? Many thanks. coef exp(coef) se(coef) robust se z Pr(>|z|) smocc_zyban -0.4384 0.6451 0.8667 0.9473 -0.463 0.644 self 1.1857 3.2728 0.1405 0.1443 8.216 2.22e-16 *** smocc_zyban:self

...#39;,'tt1','tt2','tt3','path','iters','type','length','tos','tws','time') fit<-(aov(tos~nh1*nh2*nh3*randsize*aweights*tt1*tt2*tt3*iters*length, data=expdata)) summary(fit) I want to check the fit of the model with Rsquared, but I cannot seem to find a way to do this... Any help is much appreciated... Thanks, Dorien [[alternative HTML version deleted]]

...dge into the right direction? Thanks, Joh if(m >= 0){ text( 4,0.19, cex=0.75, adj=0, paste( substitute( y == m*x+b, list( m=round(m,digits=5), b=round(b,digits=5) ) ), "\n", substitute( R^2==rsquared, list( rsquared=round(summary(fit)$r.squared,digits=3) ) ) ) ); text( 4,0.19, cex=0.75, adj=0, paste( substitute( y == m*x-b, list( m=round(m,digits=5), b=round(sqrt(b^2),digits=5) ) ),...

Dear all, I have a question about the knowing for which row I have the max value of one of my variables. I calculated the Rsquared for different columns and made a list to gather them. I unlisted this list to create a vector with this values. I want to know for which column I have the max value of Rsquared. The columns were always named in the same way. They always start with results4$depth_ following by the number. The numb...

Hi, I know that Rsquare in glm or in non-linear models is "wrong", but some people like this. How I make to estimate the Rsquare from a model ajusted with glmmPQL or another GLMM? Thanks for all Ronaldo -- A simplicidade ?? o ??ltimo degrau da sabedoria. -- Victor Hugo -- |> // | \\ [***********************************] | ( ?? ?? ) [Ronaldo Reis J??nior

I think you've badly misinterpreted the purpose of the R listserv with this request: https://www.stat.math.ethz.ch/mailman/listinfo/r-help says "The `main' R mailing list, for announcements about the development of R and the availability of new code, questions and answers about problems and solutions using R, enhancements and patches to the source code and documentation of R,

...d, data = SC, fct = LL.4()) plot(FourP, main = "LTB4 Standard Curve Zi Phase 7", xlab = "Expected (pg/mL)", ylab = "Response (%Bound)") Thanks for any help. Kevin McEnroy -- View this message in context: http://r.789695.n4.nabble.com/Adding-a-correlation-value-like-Rsquared-to-a-4-parameter-logistic-fit-model-tp3662480p3662480.html Sent from the R help mailing list archive at Nabble.com.

...{ x <- subset(curvedata,Group == i)$MPa y <- subset(curvedata,Group == i)$PLC name <- subset(curvedata,Group == i)$Sample points(x,y) vlc <- nls(y ~ 100/(1+exp(a*(x-b))), start=c(a=1, b=-3), data=list(x,y)) curve(100/(1+exp(coef(vlc)[1]*(x-coef(vlc)[2]))), col=1, add = TRUE) Rsquared <- 1 - var(residuals(vlc))/var(y) summarizeall[i ,"Run"] <- i summarizeall[i ,"Sample"] <- name[1] summarizeall[i ,"a"] <- coef(vlc)[1] summarizeall[i ,"b"] <- coef(vlc)[2] summarizeall[i ,"R2"] <- Rsquared listnow <- da...

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, Wouter Buytaer...

Hi, I've built a linear model using multiple linear regression which leads me a R-squared value of 73.58%. After that, I used this model to predicted some values based on the test data. Now I'm wondering how: 1. can I measure de R-squared value between the predicted(by the model) and real (observed) values.? 2. Measure the RMSE error . Example: suppose my data its below: REAL

Amigos de la erre. He creado mi primer bucle con for para entrenar unos modelos con GAM. La respuesta es quasipoisson porque estoy trabajando con densidades de peces. Sin embargo, tengo un problema, no se muy bien como añadir el offset a la formula siguiente cuando creo el bucle. GAM.A1 <-gam ((DYO)~s(DMA,k=4)+ s(WOD,k=4)+s(CIN,k=4)+s(DRA,k=4)+s(DBR,k=4)

To everyone, I am currently doing analysis through Splus but am having severe problems. I am trying to fit all subset weighted regression to a multivariate data set and get PRESS statistics, along with Rsquare, Rsquare adjusted and Mallows Cp for all possible models. Splus, will give me these statistics but the leaps procedure is highly sensitive to nearly singular data matrices (which mine is)

Hi, I am trying to run the command "forward.sel.par," however I receive the error message: "Error: could not find function 'simpleRDA2'." I have the vegan library loaded. The documentation on "varpart" has not helped me to understand why I cannot call this function. Maybe I am missing something obvious because I am still an 'R' novice. Below is a

...It's actually in a time series framework also but that's not relevant > for my question. My question has 2 parts : > > 1) I was leaning towards using the R squared as the decision criteria ( > I will be Regressing monthly and over a couple of years so I will have > about 24 rsquareds. I have tons of data For one monthly regression so I > don't have to just do one big regression over the whole time period ) > but I noticed in your previous example that the model with intercept ( > compared to the model forced to have zero intercept ) had a lower R^2 > and a lowe...

Hello, I'm with a conceptual doubt regarding Rsquared of both lm() and postResample(library caret). I've got a multiple regression linear model (lets say mlr) with anR² value of 67.52%. Then I use this model pro make predictions with predict() function using the same data as input , that is, use the generated model to predict the value associated...

...ies) inTrain1=createDataPartition(y=iris$Species, p=.75, list=FALSE) training1=iris[inTrain1,] testing1=iris[-inTrain1,] ctrl1=trainControl(method="cv", number=10) plsFit2=train(Species~., data=training1, method="pls", trControl=ctrl1, metric="Rsquared", preProc=c("scale")) data(iris) training1=iris[inTrain1,] datvars=training1[,1:4] dat.sc=scale(datvars) n=nrow(dat.sc) dat.indices=seq(1,n) timematrix=with(training1, classvec2classmat(Species[dat.indices])) pls.dat=plsr(timematrix ~ dat.sc, ncomp=3, method=&quot...