Thank you in advance for helping me with this.
I included a part of the actual data. The result of pred.est and
pred.est1are different, but they should be identical. For
pred.est, I entered the slope and y intercept and received a value for each
individual number in the matrix (Z). For pred.est1, I was wanting R to do
this for me and it seems that it combined values within each row of the
matrix (Z), this was indicated by the both the row numbers and pred.est1 =
30.
rm(list=ls())
#Water
w = c(9.037929, 8.273594, 9.253578, 8.039490, 8.381091, 11.610205,
11.261445, 11.185045, 9.903959, 12.307910, 10.307602, 13.950863,
13.028331, 13.677622, 13.051269, 13.289698, 14.391914, 21.411512,
75.568802, 78.168239, 60.829664, 112.558057, 127.296835, 108.739532,
133.516712, 130.492614, 129.783800, 168.289704, 152.732359, 168.405646)
#Resistance
R=c(660, 548, 676, 763, 768, 692, 657, 630, 748, 680, 786, 645, 710, 677,
692, 732, 737, 651, 396,
601, 640, 448, 464, 472, 434, 487, 495, 426, 429, 456)
#Detector length
Lend=c(37.0, 39.0, 39.0, 39.0, 40.0, 41.5, 44.0, 45.0, 46.0, 47.0,
47.0, 48.0,
48.5, 49.0, 51.0, 53.0, 53.0, 60.0, 89.0, 103.0, 108.5, 118.0, 118.0,
123.0,
126.0, 138.0, 139.0, 141.0, 141.0, 151.0)
#Errors to be multiplied by Restistance
x=c(0,.05,.10,.15,.20,.25)
#Errors to be multiplied by Detector length
y=c(0,.01,.02,.03,.04,.05)
#equation to predict water weight in grams
Rs<-(Lend^2)/R
model.lm<-lm(w~Rs)
a=predict.lm(model.lm)
X=(R%o%x+R)
Y=((Lend%o%y+Lend)^2)
X
Y
num.x.col <- length(X[1,])
num.y.col <- length(Y[1,])
num.rows <- length(X[,1])
Z <- matrix(nrow=num.rows, ncol=num.x.col*num.y.col)
for( i in 1:num.rows) {
Z[i,] <- as.vector( Y[i,] %*% t(X[i,])^-1 )
}
Z
pred.est <- 3.453*Z+1.994
pred.est1 <- predict.lm(model.lm, data.frame(Rs=Z))
pred.est
pred.est1
detach(z)
detach(sen)
On Sat, Feb 16, 2008 at 2:10 AM, Uwe Ligges <[EMAIL PROTECTED]>
wrote:
>
>
> Marlin Keith Cox wrote:
> > Z is a matrix and when I run the following line, it creates a prediction
> > estimate using each column, how can I get it an estimate for each
> individual
> > number. I have tried changing Z to a data.frame, but this does not do
> it
> > either.
> >
> > model.lm<-lm(w~x)
> >
> > pred.est <- predict.lm(model.lm, data.frame(x=Z))
>
> That's what I do and it always worked for me. Can you please specify a
> reproducible example that shows what you got and tells us exactly what
> you expected?
>
> BTW: It is expected that you call the generic predict() rather than its
> particular method.
>
> Uwe Ligges
>
>
> > Thanks in advance,
> > keith
> >
>
--
Keith Cox, Ph.D.
Sitka Sound Science Center
Fisheries Biologist
P.O. Box 464
Sitka, Alaska, 99835
907 752-0563
[EMAIL PROTECTED]
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