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