Displaying 20 results from an estimated 5000 matches similar to: "Step and stepAIC"
2007 Jun 27
1
stepAIC on lm() where response is a matrix..
dear R users,
I have fit the lm() on a mtrix of responses.
i.e M1 = lm(cbind(R1,R2)~ X+Y+0). When i use
summary(M1), it shows details for R1 and R2
separately. Now i want to use stepAIC on these models.
But when i use stepAIC(M1) an error message comes
saying that dropterm.mlm is not implemented. What is
the way out to use stepAIC in such cases.
regards,
2017 Jun 08
1
stepAIC() that can use new extractAIC() function implementing AICc
I would like test AICc as a criteria for model selection for a glm using
stepAIC() from MASS package.
Based on various information available in WEB, stepAIC() use
extractAIC() to get the criteria used for model selection.
I have created a new extractAIC() function (and extractAIC.glm() and
extractAIC.lm() ones) that use a new parameter criteria that can be AIC,
BIC or AICc.
It works as
2009 May 05
2
Stepwise logistic Regression with significance testing - stepAIC
Hello R-Users,
I have one binary dependent variable and a set of independent variables (glm(formula,…,family=”binomial”) ) and I am using the function stepAIC (“MASS”) for choosing an optimal model. However I am not sure if stepAIC considers significance properties like Likelihood ratio test and Wald test (see example below).
> y <- rbinom(30,1,0.4)
> x1 <- rnorm(30)
> x2
2003 May 08
2
Forward Stepwise regression with stepAIC and step
Dear all,
I cannot seem to get the R functions step or stepAIC to perform forward
or stepwise regression as I expect. I have enclosed the example data in
a dataframe at the end of this mail. Note rubbish is and rnorm(17) variable
which I have deliberately added to the data to test the stepwise procedure.
I have used
wateruse.lm<-lm(waterusage~.,data=wateruse) # Fit full model
2009 Feb 18
1
using stepAIC with negative binomial regression - error message help
Dear List,
I am having problems running stepAIC with a negative binomial regression model. I am working with data on manta ray abundance, using 20 predictor variables. Predictors include variables for location (site), time (year, cos and sin of calendar day, length of day, percent lunar illumination), oceanography (sea surface temp mean and std, sea surface height mean and std), weather (cos
2009 Jan 28
1
StepAIC with coxph
Hi,
i'm trying to apply StepAIC with coxph...but i have the same error:
stepAIC(fitBMT)
Start: AIC=327.77
Surv(TEMPO,morto==1) ˜ VOD + SESSO + ETA + ........
Error in dropterm.default(fit,scope$drop, scale=scale,trace=max(0, :
number of rows in use has changed: remove missing values?
anybody know this error??
Thanks.
Michele
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2005 Dec 08
1
mle.stepwise versus step/stepAIC
Hello,
I have a question pertaining to the stepwise regression which I am trying to
perform. I have a data set in which I have 14 predictor variables
accompanying my response variable. I am not sure what the difference is
between the function "mle.stepwise" found in the wle package and the
functions "step" or "stepAIC"? When would one use
2004 Mar 19
2
Odd behaviour of step (and stepAIC)?
I can only assume I'm betraying my ignorance here, but this is not what
I would expect.
I'm getting the following from a stepwise selection (with both step and
stepAIC):
> step(lm(sqrt(Grids)~ SE + Edge + NH), scope=~ (Edge + SE + NH)^2)
Start: AIC= 593.56
sqrt(Grids) ~ SE + Edge + NH
Df Sum of Sq RSS AIC
<none> 2147.0 593.6
+ Edge:NH 1
2005 Oct 24
1
Error in step() (or stepAIC) for Cox model
Hello all,
I am trying to use stepwise procedure to select covariates in Cox model
and use bootstrap to repeat stepwise selection, then record how many
times variables are chosen by step() in bootstrap replications. When I
use step() (or stepAIC) to do model selection, I got errors. Here is the
part of my code
for (j in 1:mm){ #<--mm=10
for (b in 1:nrow(reg.bs)){ #<--bootstrap 10
2003 Aug 04
1
Error in calling stepAIC() from within a function
Hi,
I am experiencing a baffling behaviour of stepAIC(),
and I hope to get any advice/help on what went wrong
or I'd missed. I greatly appreciate any advice given.
I am using stepAIC() to, say, select a model via
stepwise selection method.
R Version : 1.7.1
Windows ME
Many thanks and best regards,
Siew-Leng
***Issue :
When stepAIC() is placed within a function, it seems
2006 May 05
1
trouble with step() and stepAIC() selecting the best model
Hello,
I have some trouble using step() and stepAIC() functions.
I'm predicting recruitment against several factors for different plant
species using a negative binomial glm.
Sometimes, summary(step(model)) or summary(stepAIC(model) does not
select the best model (lowest AIC) but just stops before.
For some species, step() works and stepAIC don't and in others, it's the
opposite.
2003 Aug 27
1
Problem in step() and stepAIC() when a name of a regressors has b (PR#3991)
Hi all,
I've experienced this problem using step() and stepAIC() when a name of a
regressors has blanks in between (R:R1.7.0, os: w2ksp4).
Please look at the following code:
"x" <-
c(14.122739306734, 14.4831100207131, 14.5556459667089,
14.5777151911177,
14.5285815352327, 14.0217803203846, 14.0732571632964,
14.7801310180502,
14.7839362960477, 14.7862217992577)
2008 Oct 11
1
step() and stepAIC()
The birth weight example from ?stepAIC in package MASS runs well as
indeed it should.
However when I change stepAIC() calls to step() calls I get warning
messages that I don't understand, although the output is similar.
Warning messages:
1: In model.response(m, "numeric") :
using type="numeric" with a factor response will be ignored
(and three more the same.)
Checked
2002 Mar 01
2
step, leaps, lasso, LSE or what?
Hi,
I am trying to understand the alternative methods that are available for
selecting
variables in a regression without simply imposing my own bias (having "good
judgement"). The methods implimented in leaps and step and stepAIC seem to
fall into the general class of stepwise procedures. But these are commonly
condemmed for inducing overfitting.
In Hastie, Tibshirani and Friedman
2012 Sep 18
1
Lowest AIC after stepAIC can be lowered by manual reduction of variables
Hello
I am not really a statistic person, so it's possible i did something completely wrong... if this is the case: sorry...
I try to get the best GLM model (with the lowest AIC) for my dataset.
Therefore I run a stepAIC (in the "MASS" package) for my GLM allowing only two-variable-interactions.
For the output (summary) I got a model with 7 (of 8) variabels and 5 interactions and
2017 Aug 22
1
boot.stepAIC fails with computed formula
SImplify your call to lm using the "." argument instead of
manipulating formulas.
> strt <- lm(y1 ~ ., data = dat)
and you do not need to explicitly specify the "1+" on the rhs for lm, so
> frm2<-as.formula(paste(trg," ~ ", paste(xvars,collapse = "+")))
works fine, too.
Anyway, doing this gives (but see end of output)"
bst <-
2003 Jun 18
2
Forward stepwise procedure w/ stepAIC
I'm attempting to select a model using stepAIC. I want to use a forward
selection procedure. I have specified a "scope" option, but must not be
understanding how this works. My results indicate that the procedure begins
and ends with the "full" model (i.e., all 17 independent variables)...not
what I expected. Could someone please point out what I'm not
2017 Aug 23
0
boot.stepAIC fails with computed formula
It seems that if you build the formula as a character string, and
postpone the "as.formula" into the lm call, it works.
instead of
frm1 <- as.formula(paste(trg,"~1"))
use
frm1a <- paste(trg,"~1")
and then
strt <- lm(as.formula(frm1a),dat)
regards,
Heinz
Stephen O'hagan wrote/hat geschrieben on/am 23.08.2017 12:07:
> Until I get a fix that works, a
2003 Jun 16
1
stop criterion for stepAIC
Hello,
I am using the function stepAIC (library MASS) to run a backward
elimination on my linear regression. The new model stepAIC calculates
contains coefficients that have a Pr(>|t|) value below 0.1, but I'd
like to have only coefficients with 0.001 or below.
How can I change the stop criterion for stepAIC, so that it is more
strict? There is a parameter "steps", but it is
2011 Apr 27
1
Problem about step and stepAIC
Hello,
I am now running a multiple linear regression program, but I do not know the
difference between the command step and stepAIC.
Thanks.
Maggie
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