Displaying 20 results from an estimated 10000 matches similar to: "SoS! How to predict new values using linear regression models?"
2012 Jul 12
1
Results from mixed linear models
Dear list,
I'm quite confused when interpreting results from a mixed linear model.
For example, working on Iris data frame, I want to know the effect of
species on slope of the model "Petal.Length~Sepal.Length"
I write this :
data(iris)
reg01 <- lm(Petal.Length~Sepal.Length + Sepal.Length:Species, data=iris)
summary(reg01)
It gives me a summary table with lm for the first
2012 Jul 31
1
kernlab kpca predict
Hi!
The kernlab function kpca() mentions that new observations can be transformed by using predict. Theres also an example in the documentation, but as you can see i am getting an error there (As i do with my own data). I'm not sure whats wrong at the moment. I haven't any predict functions written by myself in the workspace either. I've tested it with using the matrix version and the
2010 Oct 19
0
RWeka - Error in model.frame.default - evaluate_Weka_classifier
Hi,
First of all, I'm a complete rookie to R (~2 weeks). But anyway, I'm
trying to use the RWeka interface for C4.5 (J48) classification.
As a proof of concept I'm using the Iris data set to create a training
set of 30 instances (10 per species) and use the remaining 120
instances as my test set.
This is what I do:
trainingIndices <- rep(1:10, 3) + rep(0:2, each=10) * 50
2006 May 02
1
Use predict.lm
Hi All,
I created a two variable lm() model
slm<-lm(y[1:3000,8]~y[1:3000,12]+y[1:3000,15])
I made two predictions
predict(slm,newdata=y[201:3200,])
predict(slm,newdata=y[601:3600,])
there is no error message for either of these.
the results are identical, and identical to slm$fitted as well.
if this is not the right way to apply the model coefficients to a new
set of inputs, what is
2012 May 05
1
No Data in randomForest predict
I would like to ask a general question about the randomForest predict
function and how it handles No Data values. I understand that you can omit
No Data values while developing the randomForest object, but how does it
handle No Data in the prediction phase? I would like the output to be NA
if any (not just all) of the input data have an NA value. It is not clear
to me if this is the default or
2012 May 04
1
weird predict function error when I use naive bayes
Hi,
I tried to use naivebayes in package 'e1071'.
when I use following parameter, only one predictor, there is an error.
> m<- naiveBayes(iris[,1], iris[,5])
> table(predict(m, iris[,1]), iris[,5])
Error in log(sapply(attribs, function(v) { :
Non-numeric argument to mathematical function
However, when I use two predictors, there is not error any more.
> m<-
2008 Feb 27
2
multiple plots per page using hist and pdf
Hello,
I am puzzled by the behavior of hist() when generating multiple plots
per page on the pdf device. In the following example two pdf files
are generated. The first results in 4 plots on one pdf page as
expected. However, the second, which swaps one of the plot() calls
for hist(), results in a 4 page pdf with one plot per page.
How might I get the histogram with 3 other scatter
2008 Oct 13
2
split data, but ensure each level of the factor is represented
Hello,
I'll use part of the iris dataset for an example of what I want to
do.
> data(iris)
> iris<-iris[1:10,1:4]
> iris
Sepal.Length Sepal.Width Petal.Length Petal.Width
1 5.1 3.5 1.4 0.2
2 4.9 3.0 1.4 0.2
3 4.7 3.2 1.3 0.2
4 4.6 3.1 1.5
2006 May 31
2
a problem 'cor' function
Hi list,
One of my co-workers found this problem with 'cor' in his code and I confirm it too (see below). He's using R 2.2.1 under Win 2K and I'm using R 2.3.0 under Win XP.
===========================================
> R.Version()
$platform
[1] "i386-pc-mingw32"
$arch
[1] "i386"
$os
[1] "mingw32"
$system
[1] "i386, mingw32"
$status
2010 Jun 09
4
question about "mean"
Hi there:
I have a question about generating mean value of a data.frame. Take
iris data for example, if I have a data.frame looking like the following:
---------------------
Sepal.Length Sepal.Width Petal.Length Petal.Width Species
1 5.1 3.5 1.4
0.2 setosa
2 4.9 3.0 1.4
0.2
2013 Jan 16
4
Get a percent variable based on group
Dear all, I'd like to get a percentage variable based on a group, but without creating a new data frame.
For example:
data(iris)
iris$percent <-unlist(tapply(iris$Sepal.Length,iris$Species,function(x) x/sum(x, na.rm=TRUE)))
This does not work, I should have only three standard values, respectively for setosa, versicolor, and virginica. How can I do this?
MANY THANKS,
Karine
2010 Nov 24
3
Límites de confianza de la mediana en distribuciones simétricas
Por si alguno pudiera ayudarme.
Al realizar el t.test para una muestra, junto con el valor de t y el
p-valor, la función proporciona la estimación de la media y su INTERVALO
DE CONFIANZA.
Desde el punto de vista de la estadística de rangos esto se puede hacer
mediante:
> iris$MEDIANA <- with(iris, 2.95)
> median(iris$Sepal.Width - iris$MEDIANA, na.rm=TRUE) # median difference
[1]
2007 Sep 19
2
By() with method = spearman
I have a data set where I want the correlations between 2 variables
conditional on a students grade level.
This code works just fine.
by(tmp[,c('mtsc07', 'DCBASmathscoreSPRING')], tmp$Grade, cor,
use='complete', method='pearson')
However, this generates an error
by(tmp[,c('mtsc07', 'DCBASmathscoreSPRING')], tmp$Grade, cor,
use='complete',
2007 Oct 09
2
lattice/xyplot: horizontal y-axis labels with scales(relation="free")
I would like to create an xyplot with varying y-axis limits and horizontal labels at the y-axis tickmarks.
The following does not seem to work, although I think it should, going by the documentation for par.
R version 2.5.1, Windows XP Prof.
Thanks for a clue.
Andreas Krause
library(lattice)
# axis labels for y-axis are horizontal
xyplot(Sepal.Length ~ Sepal.Width | Species, data=iris)
#
2012 Apr 25
1
recommended way to group function calls in Sweave
Dear all
When using Sweave, I'm always hitting the same bump: I want to group
repetitive calls in a function, but I want both the results and the
function calls in the printed output. Let me explain myself.
Consider the following computation in an Sweave document:
summary(iris[,1:2])
cor(iris[,1:2])
When using these two calls directly, I obtain the following output:
> summary(iris[,1:2])
2011 Jul 28
2
not working yet: Re: lattice overlay
Hi Dieter and R community:
I tried both of these three versions with ylim as suggested, none work: I
am getting only single (pch = 16) not overlayed (pch =3) everytime.
*vs 1*
require(lattice)
xyplot(Sepal.Length ~ Sepal.Width | Species , data= iris,
panel= function(x, y, subscripts) {
panel.xyplot(x, y, pch=16, col = "green4", ylim = c(0, 10))
panel.lmline(x, y, lty=4, col =
2009 Apr 08
2
Doubt about aov and lm function... bug?
Hi,
The below very strange:
# a) aov function
av <- aov(Sepal.Length ~ Species, data=iris)
# Error in parse(text = x) :
# unexpected symbol in "Sepal(Sepal.Length+Species)Length"
av <- aov(iris[, 1] ~ iris[, 5])
# summary(av)
# Df Sum Sq Mean Sq F value Pr(>F)
# iris[, 5] 2 63.2 31.6 119 <2e-16 ***
# Residuals 147 39.0 0.3
# ---
2012 Jul 10
3
fill 0-row data.frame with 1 line of NAs
Dear all
Is there a simpler method to achieve the following: When I obtain an
empty data.frame after subsetting, I need for it to contain one line
of NAs. Here's a dummy example:
> (.xb <- iris[ iris$Species=='zz', ])
[1] Sepal.Length Sepal.Width Petal.Length Petal.Width Species
<0 rows> (or 0-length row.names)
> dim(.xb)
[1] 0 5
> (.xa <-
2005 Sep 16
6
How do I get the row indices?
Hi,
I was wondering if it's possible to get the row
numbers from a filtering. Here's an example:
# give me the rows with sepal.length == 6.2
iris[(iris[,1]==6.2),]
# output
Sepal.Length Sepal.Width Petal.Length Petal.Width
Species
69 6.2 2.2 4.5 1.5
versicolor
98 6.2 2.9 4.3 1.3
versicolor
127 6.2
2003 Sep 09
2
lattice.xyplot: adding grid lines
Hallo,
I'd like to add grid lines to a lattice graph having 2 series of Y data.
See these 2 examples:
data(iris)
[1]
xyplot(Sepal.Length + Sepal.Width ~ Petal.Length ,
data = iris, allow.multiple = TRUE, scales = "same",type="l",
)
[2]
xyplot(Sepal.Length + Sepal.Width ~ Petal.Length ,
data = iris, allow.multiple = TRUE, scales =