similar to: Stepwise logistic Regression with significance testing - 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

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

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

Sorry, I just realized I didn't type in the correct names of the variables I am working with, this is how it should be: plot(1,1,type="n") for (i in summ$tx) { points(summ$timep[summ$tx==i],summ$mn[summ$tx==i]) lines(summ$timep[summ$tx==i],summ$mn[summ$tx==i]) } Thank you, Judith ____________________________________________________________________________________

Hi, Optimizes celt_pitch_xcorr for ARM NEON floating point. Changes from RFCv3: - celt_neon_intr.c - removed warnings due to not having constant pointers - Put simpler loop to take care of corner cases. Unrolling using intrinsics was not really mapping well to what was done in celt_pitch_xcorr_arm.s - Makefile.am Removed explicit -O3 optimization - test_unit_mathops.c,

hi all i have a function that uses two inputs, say xdata and ydata. An example is the following, simple1<-function(xdata,ydata) { ofit<-lm(ydata~xdata) list(ofit) } say i use arbitray number for xdata and ydata such that D = x1 x2 y 1 1 10 2 6 6 3 10 7 x<-D[,1:2] and y<-D[,3] if one uses these inputs and rund the program we get the following: >simple(xdata=x,ydata=y)

Hi, Optimizes celt_pitch_xcorr for floating point. Changes from RFCv1: - Rebased on top of commit aad281878: Fix celt_pitch_xcorr_c signature. which got rid of ugly code around CELT_PITCH_XCORR_IMPL passing of "arch" parameter. - Unified with --enable-intrinsics used by x86 - Modified algorithm to be more in-line with algorithm in celt_pitch_xcorr_arm.s Viswanath Puttagunta

Hi, Optimizes celt_pitch_xcorr for floating point. Changes from RFCv2: - Changes recommended by Timothy for celt_neon_intr.c everything except, left the unrolled loop still unrolled - configure.ac - use AC_LINK_IFELSE instead of AC_COMPILE_IFELSE - Moved compile flags into Makefile.am - OPUS_ARM_NEON_INR --> typo --> OPUS_ARM_NEON_INTR Viswanath Puttagunta (1): armv7:

From: Viswanath Puttagunta <viswanath.puttagunta at linaro.org> Hi, Optimizes celt_pitch_xcorr for floating point. Changes from RFCv1: - Rebased on top of commit aad281878: Fix celt_pitch_xcorr_c signature. which got rid of ugly code around CELT_PITCH_XCORR_IMPL passing of "arch" parameter. - Unified with --enable-intrinsics used by x86 - Modified algorithm to be more

Hello, I have some satellite tag time-at-depth (TAD) frequency data that I would like some help with. The data was transmitted via satellite as percent time spent in each of 7 depth bins (0m, 0-1m, 1-10m, 10-50m etc.), binned over 6-hour intervals. I categorized each row of data corresponding to a date and time into summer vs. winter, and day vs. night, and then summed and averaged the given

Hi all, I try to write a simple function in a script. The script is as follows yo<-function(Xdata) { n<-length(Xdata[,1]) Lgm<-nls(formula=LgmFormula, data=Xdata, start=list(a=1500,b=0.1),weights=Xdata$Qe) return(Lgm) } After the execution of the script, when I call the function yo on data called NC60.DATA I get an error. #yo(NC60.DATA) Erreur dans eval(expr, envir, enclos)

Hello, I received feedback from engineers working on NE10 [1] that it would be better to use NE10 [1] for FFT optimizations for opus use cases. However, these FFT patches are currently in review and haven't been integrated into NE10 yet. While the FFT functions in NE10 are getting baked, I wanted to optimize the celt_pitch_xcorr (floating point only) and use it to introduce ARM NEON

Review comments inline. > +if OPUS_ARM_NEON_INTR > +noinst_LTLIBRARIES = libarmneon.la > +libarmneon_la_SOURCES = $(CELT_SOURCES_ARM_NEON_INTR) > +libarmneon_la_CPPFLAGS = $(OPUS_ARM_NEON_INTR_CPPFLAGS) -I$(top_srcdir)/include > +endif I don't think these should be in a separate library. It brings with it lots of complications (to name one: wouldn't the .pc files need to

Dear R experts, I am sorry for sending this email again. I would imagine yesterday and maybe today, have been very busy days with the release of R v 2.7.0. I join all the R users who are very gratful for your contant work and efforts, specially knowing that you are doing this for the sake of science, without gettig any compensation for that. Having written that, I decided to send the

Hola, buenas tardes estoy intentando hacer un bootstrap de un modelo, pero me da el siguiente error: "Error in FUN(newX[, i], ...) : unused argument(s) (list(age = c(33, 47, 49, 56, 60, 64, 64, 66, 68, 69, 71, 71, 72, 73, 74, 75, 75, 76, 78, 81, 83, 83, 36, 43, 46, 47, 49, 49, 51, 51, 52, 52, 53, 54, 54, 54, 55, 56, 56, 57, 57, 58, 58, 58, 58, 59, 59, 60, 61, 62, 63, 64, 65, 65, 66, 66,

Hi everyone (again), before you all start screaming that the reordering of factors has been discusse on several threads and is not particular to ggplot2, hear me out. I can easily reorder my x-axis factor in facet.grid() in ggplot2. What I cannot reorder are the factors represented on the strips. I can see that the graphs are changing, so I am afraid of what it is I am doing. Why is ggplot2

Viswanath Puttagunta wrote: > + SUMM = vdupq_n_f32(0); It kills me that there's no intrinsic for VMOV.F32 d0, #0 (or at least I couldn't find one), so this takes two instructions instead of one. > + /* Consume 4 elements in x vector and 8 elements in y > + * vector. However, the 8'th element in y never really gets > + * touched in this loop. So, if len == 4,

Hi R-experts, I want to use the jackknife function from the bootstrap package onto a linear model. I can't figure out how to do that. The manual says the following: # To jackknife functions of more complex data structures, # write theta so that its argument x # is the set of observation numbers # and simply pass as data to jackknife the vector 1,2,..n. # For example, to jackknife #

Hi, I am parsing a C++ file using cindex.py and want to get the template parameters to a specific node. However, the tree seems to be different depending on if the template parameter is a struct/class or a simple type such as int or float. In the first case the template type is appended as a child to the VAR_DECL node (the TYPE_REF node seen in the example below), but this is not the case with

I have a set of data in the form x1, y1, z1 x1, y2, z2 ... x1, yN, zN x2, y1, z(N+1) x2, y2, z(N+2) ... x2, yN, z(2N) ...and so on... xM, yN, val(M*N) I have been trying to figure out how to get R to use this data in a persp plot. So far the only thing that I can figure out to do is to break the data file into three different files. The first file contains the x-coordinate data: x1 x2