search for: rsquare

...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) pValues<-numeric(67) #Start lists for X and Y values within each stand xi<-numeric(0) yi<-numeric(0) #Set the first element to the starting X and Y values xi[1]=X[1] yi[1]=Y[1] #Start looping working through your data, record by record for (i in 2:length(X)) { #If you ar...

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...

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.

...y Df Sum Sq Mean Sq F value Pr(>F) x 1 4062.9 4062.9 400.04 2.990e-13 *** f 1 4421.5 4421.5 435.35 1.496e-13 *** Residuals 17 172.7 10.2 --- Signif. codes: 0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 ` ' 1 > #rsquare of model > (4062.9+4421.5)/(4062.9+4421.5+172.7) [1] 0.980051 In this way I calculate the model rsquare, but how to calculate the rsquare of each levels "a" and "b"? This is only an example, the model maybe glm, lme etc. Thanks Ronaldo -- NOWPRINT. NOWPRINT. Clemclone,...

...- Signif. codes: 0 ?***? 0.001 ?**? 0.01 ?*? 0.05 ?.? 0.1 ? ? 1 exp(coef) exp(-coef) lower .95 upper .95 smocc_zyban 0.6451 1.5502 0.1008 4.130 self 3.2728 0.3055 2.4666 4.343 smocc_zyban:self 1.1529 0.8673 0.7229 1.839 Rsquare= 0.116 (max possible= 0.821 ) Likelihood ratio test= 137 on 3 df, p=0 Wald test = 114.3 on 3 df, p=0 Score (logrank) test = 141.3 on 3 df, p=0, Robust = 70.98 p=2.665e-15 -- View this message in context: http://r.789695.n4.nabble.com/max-possible-rsquare-tp3664925p3664925....

...#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 num...

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 -- |> // | \\ [...

...ntation of R, comparison and compatibility with S and S-plus, and for the posting of nice examples and benchmarks." -----Original Message----- From: Ronaldo Reis Jr. [mailto:chrysopa at insecta.ufv.br] Sent: Wednesday, August 27, 2003 10:04 AM To: R-Help Subject: Re: [R] how to calculate Rsquare Can anybody send these articles for me? > NagelKerke, N. J. D. (1991) "A note on a general definition of the > coefficient of determination", Biometrika 78: 691-2. > > Cox, D. R. and Wermuth, N. (1992) "A comment on the coefficient of > determination for bi...

...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 <- d...

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 Buytae...

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

...Summ <- summary(GAM) Var.p.values <- Summ$s.table[,"p-value"] MaxSignif <-c(MaxSignif,max(Var.p.values)) Significance <- all(Var.p.values<0.1) ### Especificar el p values que queremos dentro del modelo GlobalSignificance <- c(GlobalSignificance,Significance) RSquare <- c(RSquare,Summ$r.sq) } Si teneis alguna sugerencia os estaría muy agradecido -- *Juan Diego Alcaraz Hernández * ** *http://juandiegoalcaraz.wordpress.com/* * Institut d'Investigació per a la Gestió Integrada de Zones Costaneres (IGIC) Universitat Politècnica de València C/ Paranimf, 1...

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) and the Rsquare and adjusted Rsquare values it gives me are biased high (seems to be the case whenever you use...

...s function implements FS using the F-test described ## by Miller and Farr (1971). This test requires that ## -- the Y variables be standardized, ## -- the error in the response variables be normally distributed (to be verified by the user). ## ## This function uses 'simpleRDA2' and 'RsquareAdj' developed for 'varpart' in 'vegan'. ## ## Pierre Legendre & Guillaume Blanchet, May 2007 ## ## Arguments -- ## ## Y Response data matrix with n rows and m columns containing quantitative variables. ## X Explanatory data matrix with n rows 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 low...

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 associate...

...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=&quo...