search for: lm11

Displaying 5 results from an estimated 5 matches for "lm11".

Did you mean: lm01
2007 Oct 29
1
lm design matrix bug?
...on these 21 obs, but the design matrix that comes out has 26 rows? Thanks for your enlightenment. Toby y = c() x1 = c() x2 = c() idx = 1 for (i in 1:3) { for (j in 1:3) { for (k in 1:3) { y[idx] = 30*i+10*j+100*i*j+30*k-60 x1[idx] = i x2[idx] = j idx = idx+1 } } } lm11 = lm(y ~ factor(x1)*factor(x2), x=1) summary(lm11) unique(predict(lm11)) X = lm11$x; X P = solve(t(X)%*%X) %*% t(X); round(P,3) y[3] = NA y[6] = NA y[12] = NA y[18] = NA y[24] = NA y[27] = NA lm21 = lm(y ~ factor(x1)*factor(x2), x=1) summary(lm21) unique(predict(lm21)) X = lm21$x; X P = solv...
2008 May 16
1
autocorrelation error: cannot allocate vector of size 220979 Kb
Dear R community, I used a linear mixed model (named lm11) to model daily soil temperature depending upon vegetation cover and air temperature. I have almost 17,000 observations for six years. I can not account for autocorrelation in my model, since I receive the error message after applying the function: update(lm11, corr=corAR1()) Error: cannot...
2008 May 16
1
autocorrelation in nlme; Error: cannot allocate vector of size
Dear R community, I used a linear mixed model (named lm11) to model daily soil temperature depending upon vegetation cover and air temperature. I have almost 17,000 observations for six years. I can not account for autocorrelation in my model, since I receive the error message after applying the function: update(lm11, corr=corAR1()) Error: cannot...
2008 May 17
0
autocorrelation in nlme: Error: cannot allocate vector of size 220979 Kb
Dear R community, Below you may find the details of my model (lm11). I receive the error message "Error: cannot allocate vector of size 220979 Kb" after applying the autocorrelation function update(lm11, corr=corAR1()). lm11<-lme(Soil.temp ~ Veg*M+Veg*year, data=a, random = list(Site=pdDiag(~Veg),...
2002 Sep 14
0
p.s. regarding stripchart missing-data report (PR#2019)
....sm ~ stai.score) #anova(lm7) #lm8 <- lm(deviat.logo.sm ~ worry.numbers.sm) #anova(lm8) #lm9 <- lm(minrisk.numbers.sm ~ truste.score+mss.m.score+worry.numbers.sm+stai.score) #anova(lm9) lm10 <- lm(minrisk.numbers.sm ~ truste.score+mss.m.score+worry.numbers.sm+sex+educ+age) anova(lm10) lm11 <- lm(minrisk.numbers.sm ~ truste.score+worry.numbers.sm) anova(lm11) #lm12 <- lm(nprob.m[,1,5,9] ~ worry.numbers.sm+pc.had+stai.score) #anova(lm12) #lm 13-15 used above # tells you which Ss said both #apply((minrisk.m==1 & exagg.m==1)+0,1,sum,na.rm=T) toohigh.sm <- apply(nprob.m&...