similar to: multivariate multi regression

Jonathan Lennox wrote: > +opus_int32 silk_noise_shape_quantizer_short_prediction_neon(const opus_int32 *buf32, const opus_int32 *coef32) > +{ > + int32x4_t coef0 = vld1q_s32(coef32); > + int32x4_t coef1 = vld1q_s32(coef32 + 4); > + int32x4_t coef2 = vld1q_s32(coef32 + 8); > + int32x4_t coef3 = vld1q_s32(coef32 + 12); > + > + int32x4_t a0 = vld1q_s32(buf32 -

> On Dec 19, 2015, at 10:07 PM, Timothy B. Terriberry <tterribe at xiph.org> wrote: > > Jonathan Lennox wrote: >> +opus_int32 silk_noise_shape_quantizer_short_prediction_neon(const opus_int32 *buf32, const opus_int32 *coef32) >> +{ >> + int32x4_t coef0 = vld1q_s32(coef32); >> + int32x4_t coef1 = vld1q_s32(coef32 + 4); >> + int32x4_t coef2 =

Hello, I've written a simple (although probably overly roundabout) function to test whether two regression slope coefficients from two linear models on independent data sets are significantly different. I'm a bit concerned, because when I test it on simulated data with different sample sizes and variances, the function seems to be extremely sensitive both of these. I am wondering if

Dear all: I'm trying to fit the optimal Box-Cox transformation related to nls (see the code below) for the demand of money data in Green (3th Edition) but in the last step R gives the next error message. Error en `[.data.frame`(eval(object$data), , as.character(formula(object)[[2]])[2]) : undefined columns selected. ?Any idea to solve the problem? Thanks in advance,

--- Makefile.am | 8 +++-- silk/NSQ.c | 37 ++++++++-------------- silk/NSQ.h | 70 +++++++++++++++++++++++++++++++++++++++++ silk/arm/NSQ_neon.c | 64 +++++++++++++++++++++++++++++++++++++ silk/arm/NSQ_neon.h | 91 +++++++++++++++++++++++++++++++++++++++++++++++++++++ silk/x86/NSQ_sse.c | 2 +- silk/x86/main_sse.h | 3 +- silk_headers.mk | 2 ++ silk_sources.mk

--- Makefile.am | 5 +-- silk/NSQ.c | 37 ++++++++-------------- silk/NSQ.h | 70 +++++++++++++++++++++++++++++++++++++++++ silk/arm/NSQ_neon.c | 64 +++++++++++++++++++++++++++++++++++++ silk/arm/NSQ_neon.h | 91 +++++++++++++++++++++++++++++++++++++++++++++++++++++ silk/x86/NSQ_sse.c | 2 +- silk/x86/main_sse.h | 3 +- silk_headers.mk | 2 ++ silk_sources.mk

As promised, here's a re-send of all my Aarch64 patches, following comments by John Ridges. Note that they actually affect more than just Aarch64 -- other than the ones specifically guarded by AARCH64_NEON defines, the Neon intrinsics all also apply on armv7; and the OPUS_FAST_INT64 patches apply on any 64-bit machine. The patches should largely be independent and independently useful, other

Hi, I have a question about running multiple in regressions in R and then storing the coefficients. I have a large dataset with several variables, one of which is a state variable, coded 1-50 for each state. I'd like to run a regression of 28 select variables on the remaining 27 variables of the dataset (there are 55 variables total), and specific for each state, ie run a regression of

This sequence of patches provides arm64 support for Opus. Tested on iOS, Android, and Ubuntu 14.04. The patch sequence was written on top of Viswanath Puttagunta's Ne10 patches, but all but the second ("Reorganize pitch_arm.h") should, I think, apply independently of it. It does depends on my previous intrinsics configury reorganization, however. Comments welcome. With this and

Here are my aarch64 patches rebased to the current tip of Opus master. They're largely the same as my previous patch set, with the addition of the final one (the Neon fixed-point implementation of xcorr_kernel). This replaces Viswanath's Neon fixed-point celt_pitch_xcorr, since xcorr_kernel is used in celt_fir and celt_iir as well. These have been tested for correctness under qemu

Following Tim's comments, here are my reworked patches for the Neon intrinsic function patches of of my Aarch64 patchset, i.e. replacing patches 5-8 of the v2 series. Patches 1-4 and 9-18 of the old series still apply unmodified. The one new (as opposed to changed) patch is the first one in this series, to add named constants for the ARM architecture variants. There are also some minor code

> > So i guess from your prev. email the svmModel$coefs correspond to the > "Alpha" . yes (times the sign of y!). > > Why do I see three columns in the coefs?( Is this the number of classes -1 > = Numbe of hyperplanes) yes, but in a packed format which is not trivial. I attach some explanation I sent to R-help some time ago (the guy wanted to write his own

Hi, I read data from a file. I'm trying to understand how to use Design.rcs by using simple test data first. I use 1000 integer values (1,...,1000) for x (the predictor) with some noise (x+.02*x) and I set the response variable y=x. Then, I try rcs and ols as follows: m = ( sqrt(y1) ~ ( rcs(x1,3) ) ); #I tried without sqrt also f = ols(m, data=data_train.df); print(f); [I plot original

On Nov 23, 2015, at 12:04 PM, John Ridges <jridges at masque.com<mailto:jridges at masque.com>> wrote: Hi Jonathan. I really, really hate to bring this up this late in the game, but I just noticed that your NEON code doesn't use any of the "high" intrinsics for ARM64, e.g. instead of: int32x4_t coef1 = vmovl_s16(vget_high_s16(coef16)); you could use: int32x4_t coef1

Hi, I've a directory of large log files (> 100M) that I want to rsync to another server in short intervals (say every minute). With the --append option I can avoid resending whole files at every sync. But rsync still calculates the checksum over the complete files every time, which claims a significant share of CPU and IO resources. Since the log files are always written in append-only

Hi, I am currently working with the sem package in R, to create pathway diagrams. Id like to use the standardized path coeffcients. To get these, I use std.coef. However, using this yields only the standardized coefficients, but does not give me the standard error. Does someone know how to get std.coef to show the standard error of the standardized path coefficients as well? Thanks, Bastiaan

Bastiaan Timmer wrote: ... > In a > previous message I mentioned writing some more convenience functions, but on > closer inspection they would either be inefficient or very difficult > to implement. Could you briefly list these, in case somebody else wants to have a go. Many thanks, Martin -- Martin J Leese E-mail: martin.leese stanfordalumni.org Web:

I'm trying to fit a Cox proportional hazards model to some hospital admission data. About 25% of the patients have had at least one admission, and of these, 40% have had two admissions within the 12 month period of the study. Each patients has had one of 4 treatments, and one of the treatment groups has had no admissions for the period. I used:

> From: Cristian Rodr?guez <crrodriguez at opensuse.org> > Sent: Sunday, May 6, 2012 8:24 AM > > El 05/05/12 02:23, Bastiaan Timmer escribi?: >> The attached patch adds the missing FLAC__metadata_object_seektable_*() >> functions from FLAC's metadata object methods (FLAC/metadata.h) to >> FLAC++'s SeekTable class. Of the 11 functions in the C API,

Ok so if I have a function: functest<-function(x){ a<-x+1 b<-x+2 c<-x+3 paste(a) paste(b) paste(c) } Now I know I can do cat(), or return() on one of them but if I was to run the function with any number, how could I create objects to save so I could do, I am wondering if I have more than one object within my function. functest$a