similar to: comparing predicted sequence A'(t) to observed sequence A(t)

Hello, I have a hierarchical dataset of this form and am trying to analyze it in R. 1 subject Tested under 2 conditions: A and B 10 sesssions in each condition In each session, 2 kinds of tests: Test 1 and Test 2 200 independent repetitions of each test-type, with 200 Yes/No answers So I think this is a 2 x 2 x 10 x 2 setup What I want to know is whether the difference in percentage of yes

Dear R-Experts, seek your help. There are two parts I want to deal with. 1) I want to create a time interval of say, 30 minutes starting from "00:00:00" hrs Thus at the end, I want to create sequence: 00:00:00 00:30:00 01:00:00 01:30:00 .. .. How to do so ? Later, I want to change the time-increment value in a variable and changing the value of this variable, I would like to create

Hello I'm trying to use C random generator function drand48() which return floating-point values, uniformly distributed over [0,1], (http://www.opengroup.org/onlinepubs/007908799/xsh/drand48.html). When values are returned to R, they are not in [0,1]. A simple C program using drand48() gives values in [0,1] so I suppose there is a problem (type definition ?) between C and R. Here are R

Thank you so much for your help. The function "dbinom" seems to work very well. However, I'm a bit lost with the "dnorm" function. Apparently, I have to compute the mean "mu" and the standard deviation "sd" but what does it mean exactly? I only have a vector of predicted response and a vector of observed response that I would like to compare! What

Hi, I've two fitted models, one binomial model with presence-absence data that predicts probability of presence and one gaussian model (normal or log-normal abundances). I would like to evaluate these models not on their capability of adjustment but on their capability of prediction by calculating the (log)likelihood between predicted and observed values for each type of model. I found

Hi, I am trying to make a palaeoenvironmental transfer function using the R package rioja that predicts the water-table (measured as depth to the water table) of an area given the testate amoebae that are found there. I've carried out weighted averaging of the data and am trying to produce a graph that shows the observed water-table versues the model's predicted values. Following the

Hi, stepAIC generic plot function creates useful graphics for the diagnosis of multiple regressions. To create predicted versus observed plots, I use to look for the coefficients, copy them by hand, calculate R?, then plot. Is there a more automated way to plot predicted versus observed with its associated R? output using stepAIC, or another function? Kind regards, S.-?. Parent Universit?

The direct cause of this issue is that, previously lld converted common symbols to defined symbols before passing input files to LTO, and after r360841 they are passed as common symbols to LTO. Making lld to work as before is easy, as we can convert common symbols to defined symbols as before. Here is a patch to do that, and I confirmed that that restores the original behavior for the reported

Hi Suresh, thanks for reporting this! I thought I fixed this with 8d94d3c3b44c3a27a69b153cef9be4b8e481150e. Did you run before or after that commit? Cheers, Johannes On 5/15/20 7:17 AM, Mani, Suresh via llvm-dev wrote: > [AMD Public Use] > > Hi , > > Please ignore the earlier header of Internal and Official use only. > > Thanks > M Suresh > > From: llvm-dev

Thanks for the info Teresa, Regards M Suresh From: Teresa Johnson <tejohnson at google.com> Sent: Thursday, June 20, 2019 7:15 PM To: Mani, Suresh <Suresh.Mani at amd.com> Cc: Rui Ueyama <ruiu at google.com>; llvm-dev <llvm-dev at lists.llvm.org> Subject: Re: [llvm-dev] Expected behavior of lld during LTO for global symbols (Attr Internal/Common) [CAUTION: External

Please provide the input file that produces this with opus_demo. On 16/04/15 03:24 AM, Suresh Thiriveedi wrote: > Hi Jean-Marc, > > Could you please update if you got a chance to look into. As I > mentioned, I don't see the same issue in 1.1.1, but I don't see any > difference in 1.1.1 other than optimization based on the architecture. > This optimization could have

To be decodable by opus_demo, you'll have to add the 8-byte "header". Just put in the length of the packet followed by "0" for the encoder range (0 means "not present"). That being said, from previous experience, the most likely cause of the crash is a bug in your software causing a corruption in Opus. So it's safe to assume that if you can't reproduce

Hi Teresa, Can you please let me know if there is any update on this issue. Thanks M Suresh From: Teresa Johnson <tejohnson at google.com> Sent: Tuesday, June 11, 2019 7:23 PM To: Rui Ueyama <ruiu at google.com> Cc: Mani, Suresh <Suresh.Mani at amd.com>; llvm-dev <llvm-dev at lists.llvm.org> Subject: Re: [llvm-dev] Expected behavior of lld during LTO for global symbols

Hello R users, I have a puzzle with the VGAM package, on my first excursion into generalized additive models, in that this very nice package seems to want to do either more or less than what I want. Precisely, I have a 4-component outcome, y, and am fitting multinomial logistic regression with one predictor x. What I would like to find out is, is there a single nonlinear function f(x) which acts

Hi, When we pass around 9K samples of only ambient noise (no voice), the encoder which is enabled FEC+DTX is detecting only some 140 frames as non-voice (returning only TOC, no frame content). We were expecting all or more to be identified as non-voice. Our idea was to check how the decoder re-generates the original ambient noise during the silence duration (when we feed NULL to decoder) when

Dear samba team, What I noticed from the below example is , any user who has write access to share are able to change sub folder acls in it. we don't want that. how to restrict this to only admin users in NAS and to AD administrator in windows. ?. Please help . ---------------- 1) Import user from W2K3 R2 Server and set up a secure share. User has Read/Write access. 2)

Red Hat Enterprise Linux Server release 6.4 (Santiago) gcc version 4.4.7 20120313 (Red Hat 4.4.7-3) (GCC) We see the issue in all our Intel based Linux servers. Thanks Suresh On 21 April 2015 at 12:41, Jean-Marc Valin <jmvalin at jmvalin.ca> wrote: > Still can't reproduce. What OS and compiler version? > > Jean-Marc > > On 21/04/15 02:48 AM, Suresh Thiriveedi

To: cran at r-project.org Subject: New package: pomp, inference for partially-observed Markov processes The new package 'pomp' is built around a very general realization of nonlinear partially-observed Markov processes (AKA state-space models, nonlinear stochastic dynamical systems). The user provides functions specifying the model's process and measurement components. The

To: cran at r-project.org Subject: New package: pomp, inference for partially-observed Markov processes The new package 'pomp' is built around a very general realization of nonlinear partially-observed Markov processes (AKA state-space models, nonlinear stochastic dynamical systems). The user provides functions specifying the model's process and measurement components. The

Hi, There is no change in the compiler flags. I'm using as it is from the original code. No change in the Makefile and I believe it is using the floating point only by default. We are using 8k samples and mono so the commands is as follows. [root at MEDIA opus-1.1]# ./opus_demo -d 8000 1 opus_encoded_crash.opus opus_encoded_crash.pcm *And segmentation is as below..*. ............ Calling