similar to: Converting POSIXct vales to real values

I have a data frame (morgan) of hourly river flow, river levels and wind direction and speed thus: Time hour lev.morgan lev.lock2 lev.lock1 flow direction velocity 1 2009-07-06 15:00:00 15 3.266 3.274 3.240 1710.6 180.282 4.352 2 2009-07-06 16:00:00 16 3.268 3.272 3.240 1441.8 192.338 5.496 3 2009-07-06 17:00:00 17 3.268

I have a dataset relating the effects of engineering works on the level of salinity in a river before and after the works. I have modelled this using linear mixed effects models to determine if the significance and level of the response to the works. I am wanting to calculate the se of difference at several points. I am not sure of how to calculate the difference and which estimate of se I

Is there an equivalent package for mixed linear effects models developed using the package "nlme" as there is for linear models? Tschüß Tony Meissner Principal Scientist (Monitoring/Statistics) Resource Monitoring Science, Monitoring and Information Division Department for Water "Imagine" © *(ph) (08) 8595 2209 *(mob) 0401 124 971 *(fax) (08) 8595 2232 * 28 Vaughan Terrace,

I have the following function defined as below match.trace <- function(dfobj, distance, day1, day2) { day1 <- substitute(dfobj$day1); day1 day2 <- substitute(dfobj$day2) distance <- substitute(dfobj$distance) xx <- NULL for (i in 0:10) xx[i+1] <- with(dfobj, cor(Lag((day1-day1[1]),i), (day2-day2[1]), use='pair')) i <- match(max(xx), xx) with(dfobj, {

dear all. Would someone be kind and willing to explain the code below for a person who has never used R? ( that is if one has enough time and inclination) It implements gillepsie's stochastic algorithm for Lotka Volterra model. What would help me tremendously is to see the breakdown of the line by line code into plain english. thanks for any insights or other comments. sean

Hi, I realized that when I have irregular series to feed into lineChart, the interval of each point in the chart does not seem to take care of irregular time interval I specified in my input xts time series. But rather, lineChart seems to take each point as equal spaced time series. For example, I have the following code: library(quantmod) options(digits.sec=3) t0 <-

Dear R-users I am trying to "vectorize" a function so that it can handle two vectors of inputs. I want the function to use phi (a function), k[1] and t[1] for the first price, and so on for the second, third and fourth price. I tried to do the mapply, but I dont know how to specify to R what input I want to be vectors (k and t)(see in the bottom what I tried). I have read the help file,

Dear R-help list, I am working on an optimization with R by evaluating a likelihood function that contains lots of Gamma calculations (BGNBD: Hardie Fader Lee 2005 Management Science). Since I am forced to implement lower bounds for the four parameters included in the model, I chose the optim() function mith L-BFGS-B as method. But the likelihood often returns inf-values which L-BFGS-B

Hi I'm trying to replicate Smith et al.'s (http://www.sciencemag.org/content/330/6008/1216.abstract) findings by fitting their Gompertz and logistic models to their data (given in their supplement). I'm doing this as I want to then apply the equations to my own data. Try as a might, I can't quite replicate them. Any thoughts why are much appreciated. I've tried contacting the

> > >What do you recommend for keeping track of user >activities? For preserving bash histories I followed >these recommendations: > >http://www.defcon1.org/secure-command.html > Interesting reading but, as others have noted, of limited use. Keystroke logging can be disabled by - as others have noted - either spawning another (perhaps different) shell, using a remote

This concerns whether p-values from lmer can be trusted. From simulations, it seems that lmer can produce very small, and probably spurious, p-values. I realize that lmer is not yet a finished product. Is it likely that the problem will be fixed in a future release of the lme4 package? Using simulated data for a quite standard mixed-model anova (a balanced two-way design; see code for the

Hi all, I have a dataset of individuals where the variable ID corresponds to the identification of the household where the individual lives. rel.head stands for the relationship with the household head. so rel.head=1 is the household head, rel.head=2 is the spouse, rel.head=3 is the children. Here is an example to see how it looks like: df<-data.frame(ID=c("17100",

hi all, out of a matter of fact I am still using llvm version 1.5. I don't know how 1.6 works in this matter. When translating a complex c application to llvm bytecodes, some semantics are lost: Take for isntance the interesting attribute to put a variable in the thread local data section (.tdata), this would be interesting to have in llvm. like in GCC you write: int x

Source: xen Severity: grave Tags: security Hi, the following security issues apply to Xen in jessie: CVE-2014-5146,CVE-2014-5149: https://marc.info/?l=oss-security&m=140784877111813&w=2 CVE-2014-8594: https://marc.info/?l=oss-security&m=141631359901060&w=2 CVE-2014-8595: https://marc.info/?l=oss-security&m=141631352601020&w=2 Cheers, Moritz

Desde la Sección de Apoyo Estadístico del Servicio de Apoyo a la investigación (SAI) de la Universidad de Murcia, te invitamos al Taller que impartiremos el próximo _26 de Marzo de 16h a 20h_, titulado : /"Shiny. Entornos web con R"/ * Lugar:* Aula *Bisbita* en la *Fac de Biología*, a las 16:30h _Se podrá seguir en directo vía streaming_ Reserva tu puesto desde caldum

https://bugzilla.samba.org/show_bug.cgi?id=5343 Summary: rsync does nothing after first time Product: rsync Version: 3.0.0 Platform: IA64 OS/Version: Linux Status: NEW Severity: normal Priority: P3 Component: core AssignedTo: wayned@samba.org ReportedBy: rolmol@broadpark.no

On Wed, Nov 19, 2014 at 11:45:02PM +0100, Moritz Muehlenhoff wrote: > Source: xen > Severity: grave > Tags: security > > Hi, > the following security issues apply to Xen in jessie: > > CVE-2014-5146,CVE-2014-5149: > https://marc.info/?l=oss-security&m=140784877111813&w=2 > > CVE-2014-8594: >

Buenas tardes, tengo dudas con el siguiente ejercicio que me han propuesto en un curso, no se si alguien podria indicarme como abordarlo, soy nueva en R y agradezco mucho su ayuda Identi car cuales son las variables que están contenidas en el data.frame. A continuación, transformar ese data.frame para que cada columna represente cada una de las variables. Usar los nombres Date, District y N.

Hi, all. I set up a dht system, and sent a HUP signal to client to trigger the reconfiguration. But i found that the TCP connection established increased by the number of bricks(the number of glusterfsd progress). $ ps -ef | grep glusterfs root 8579 1 0 11:28 ? 00:00:00 glusterfsd -f /home/huz/dht/server.vol -l /home/huz/dht/server.log -L TRACE root 8583 1 0 11:28 ?

Hi, I am trying to test the proportional-odds model using the "polr" function in the MASS library with the dataset of "housing" contained in the MASS book ("Sat" (factor: low, medium, high) is the dependent variable, "Infl" (low, medium, high), "Type" (tower, apartment, atrium, terrace) and "Cont" (low, high) are the predictor variables