similar to: fit linear regression with multiple predictor and constrained intercept

Hi, I have a set of locations defined by longitude and latitude (in degrees), and want to calculate the spatial (or geographic) distance among all locations. I did not find such a function in the spatial-related packages. (I *cannot* use 'dist', as I have geographic, not cartesian coordinates). thanks! Robert Robert Ptacnik Norwegian Institute for Water Research (NIVA) Gaustadall?en 21

Hei, I have two spatial datasets Sa and Sb, both with lat-lon coordinates and from same geographic area, but from different localities within the area (independent samples). Sa is biotoc data, Sb is some environmental parameter (fertility). I 'know' that Sb affects Sa, but wonder on which scale. I tried different interpolations by creating different grids of Sb (e.g. 20x20 and 100x100

Hei Group, I want to compare the relative importance of predictors in a multiple linear regression y~a+bx1+cx2... However, bptest indicates heteroskedasticity of my model. I therefore perform a robust regression (rlm), in combination with bootstrapping (as outlined in J. Fox, Bootstrapping Regression Models). Now I want to compare the relative importance of my predictors. Can I rely on the

Dear Listers, I have a regression problem (x->y) with biological data, where x influences y in two ways, (1) y increases with x and (2) the variation around the mean (residuals) decreases with increasing x, i.e. y becomes more 'predictable' as x increases. The relationship is saturating, y~a + bx + cx^2, gives a very good fit. I know basically how to test for heteroscedasticity. My

Dear R-listers Is there anyone who knows why I get different eigenvectors when I run MatLab and R? I run both programs in Windows Me. Can I make R to produce the same vectors as MatLab? #R Matrix PA9900<-c(11/24 ,10/53 ,0/1 ,0/1 ,29/43 ,1/24 ,27/53 ,0/1 ,0/1 ,13/43 ,14/24 ,178/53 ,146/244 ,17/23 ,15/43 ,2/24 ,4/53 ,0/1 ,2/23 ,2/43 ,4/24 ,58/53 ,26/244 ,0/1 ,5/43) #R-syntax

I am struiggling a bit with this function 'hatvalues'. I would like a little more undrestanding than taking the black-box and using the values. I looked at the Fortran source and it is quite opaque to me. So I am asking for some help in understanding the theory. First, I take the simplest case of a single variant. For this I turn o John Fox's book, "Applied Regression Analysis

dear listers, I use gam (from mgcv) for evaluation of shape and strength of relationships between a response variable and several predictors. How can I interpret the 'F' values viven in the GAM summary? Is it appropriate to treat them in a similar manner as the T-statistics in a linear model, i.e. larger values mean that this variable has a stronger impact than a variable with smaller F?

Dear R-listers I wonder if someone can help me with the syntax for the random effect in glmmPQL()? I have a data set with a response variable "y" (counts), two dependent variables: "treat" (4 levels) and "site" (2 levels). The latter, I want to use as a random variable. How do I specify this in the function? Is it like this:

Hi all! I have a problem setting ACLs on a remote file on a Windows XP Pro SP2 box. I issue the following command: smbcacls -a 'ACL:BBI-DEV\beakid:ALLOWED/0/0x00100116' -U 'BBI-DEV \Admin' //BBI-DEV/Data /Niva.txt And I get this response from debug level 3. Password: Connecting to host=BBI-DEV Connecting to 192.168.1.124 at port 445 Doing spnego session setup (blob

Hi all! I have a problem setting ACLs on a remote file on a Windows XP Pro SP2 box. I issue the following command: smbcacls -a 'ACL:BBI-DEV\beakid:ALLOWED/0/0x00100116' -U 'BBI-DEV \Admin' //BBI-DEV/Data /Niva.txt And I get this response from debug level 3. Password: Connecting to host=BBI-DEV Connecting to 192.168.1.124 at port 445 Doing spnego session setup (blob

Dear R-listers I'm a new R-user who needs some help with a test that I want to do. I have done a field experiment: four treatments (cont, x, y and xy) at three sites (A, B and C), the response is count data (0 - 15). I've done a Poisson regression: >glm(response~as.factor(treatment)*as.factor(site), family=quasipoisson, offset(max.response), data=dat) The "offset" is the

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 For those interested in some more detail of the EventLog features in the upcoming Samba 3.0.21 release, see: http://www.samba.org/~jerry/Samba-EventLog-HOWTO.txt Thanks to Brian Mroan and Marcin Porwit at Centeris for all their hard work. cheers, jerry -----BEGIN PGP SIGNATURE----- Version: GnuPG v1.4.0 (GNU/Linux) Comment: Using GnuPG with

Hi, I would like to query the X86InstrInfo tables to determine if a given opcode is a load or store from stack. I see functions isFrameLoadOpcode and isFrameStoreOpcode in lib/Target/X86/X86InstrInfo.cpp that would provide the functionality I am looking for. However, these functions are static. What is the recommended way to perform such queries for a MachineInstr - short of replicating the

Hi, This is the time series data collected from 2001 to 2008 by every month.so,there are 96 entries.I have done basic statistics.I need to find a model fitted to forecast this data.This is the mixedpaper collection for recycling in the campus. 13251 13754 19061 12631 17414 21350 25384 23646 20312 20740 14007 17175 13910 17191 17113 20250 35003 11975 19665 20490 20436

Hello everyone, I have been doing a binary classification using random forest from the library "randomForest". One of the predictors is a factor variable, which is known to be highly related to the binary response I am trying to predict. Other 80 predictors are numeric. Totally I have 44 subjects. However, the random forest returns the factor variable as the least important one based on

Hi all, I am applying a Presence/absence Generalized additive model to model the distribution of marine algae species in R. I have found that log transforming the environmental variables improves the explained deviance of the model considerably. While log transforming is common practice in GLM, I have been unable to find any papers where this is performed in a GAM. Im wondering whether this

I?m running a model on animal behavior in response to shipping. In most cases, there is only one ship in the study area at one time. Ship length, distance from the animals, speed, angle from animals, and ship direction (as east/west bound) are among shipping-related covariates (with multiple interactions). The tricky part is that sometimes there are 2 ships in the area. I could add all the same

Hi Michael, > -----Original Message----- > From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of Michael > Friendly > Sent: Thursday, June 29, 2017 9:04 AM > To: Beno?t PELE <benoit.pele at acoss.fr>; r-help at r-project.org > Subject: Re: [R] Help : glm p-values for a factor predictor > > On 6/29/17 11:13 AM, Beno?t PELE wrote: > > My question is

On 9 May 2018 at 19:48, Dávid Bolvanský via llvm-dev <llvm-dev at lists.llvm.org> wrote: > But a fix needs to be made since branch predictor hints are broken in a > valid C++20 code: They don't affect performance in the expected way, but they also don't actually break code. I'm not saying it's not a bug, but it's certainly not on the same level as a miscompilation.

On 04 Jan 2011, at 08:30, Jakob Stoklund Olesen wrote: > I noticed that we generate code like this for i386 PIC: > > calll L0$pb > L0$pb: > popl %eax > movl %eax, -24(%ebp) ## 4-byte Spill > > I worry that this defeats the return address prediction for returns > in the function because calls and returns no longer are matched. According to benchmarks by