similar to: GFI en modelos estructurales con lavaan

Dear R users, I am trying to simulate some multitrait-multimethod models using the packages sem and psych but whatever I do to deal with models which do not converge I always get stuck and get error messages such as these: "Error in summary.sem(M1) : coefficient covariances cannot be computed" "Error in solve.default(res$hessian) : System ist f?r den Rechner singul?r: reziproke

Hello, I am trying to create parcels for a CFA model. I am trying to average 6 sets of 3 variables each into parcels. I don't understand why I am getting an error message as follows: Thanks for your help, Catherine atds1par <- rowMeans(semHW1dat1[, c("atds1", "atds2", "atds3")], na.rm=TRUE) atds2par <- rowMeans(semHW1dat1[, c("atds4",

Hola a todos: Necesito saber si alguien tiene alguna idea de un paquete con múltiples funciones (cálculos) para determinar el tamaño de la muestra (particularmente de estudios de psicología y ciencias sociales). De antemano agradezco la atención. Saludo desde Brasil *Guilherme Amorim Homem de Abreu Loureiro* Agronomist Engineer *CREA-BA: 051511013-2* Master of Science in Crop Production, Soil

On 6/5/2015 1:33 PM, Michael Hennebry wrote: > It's a desktop in an old house. > The outlets have ground-fault protection, > but the third prong is ungrounded. > not sure how GFI would function at all without a valid ground, unless the GFI is wired to neutral, which is dangerous on its own. you might get a 3-prong-to-2-prong adapter and plug the PC into that, leaving the ground

On Fri, 5 Jun 2015, g wrote: > On 06/05/2015 03:43 PM, John R Pierce wrote: >> On 6/5/2015 1:33 PM, Michael Hennebry wrote: >>> It's a desktop in an old house. >>> The outlets have ground-fault protection, >>> but the third prong is ungrounded. >> >> not sure how GFI would function at all without a valid ground, unless >> the GFI is wired

Gracias por la ayuda Jose Luis. pero o no te he entendido bien o mi duda es tan sencilla que no me he explicado. SI yo tampoco he entendido mal tu explicación, mi problema es cómo obtengo ese "tus.pesos" para introducir, por ejemplo, en la función: library(survey) # objeto del diseño muestral ddatos <- svydesign(id=~1, weights =~ tus.pesos, data = tus.datos) # en caso de una reg

I'm working on the code to handle GC tracing of "intermediate values" (as described in the GC doc), and I've run into a weird problem. (Note, this has nothing to do with the patch I have proposed, this error occurs with regular old pointer-allocas.) The exception I am getting occurs in this code here in SelectionDAGBuilder.cpp: *case* *Intrinsic*::gcroot: *if* (GFI) {

Hola, ¿qué tal? Cierto, cierto, había un error en el código que publiqué. Pero el diagnóstico es parecido. Cuando los datos se generan con el coeficiente de x2 igual a 7, los coeficientes estimados tienen una distribución extraña, bimodal (aparentemente), en lugar de _normalmente_ distribuida alrededor del 7 como se espera. Supongo que depende del número de casos en que x2 = 1 e y = 0. Un

I have a x100p card that has call waiting on the line comming into it and then into *..... is there any way i can use call waiting on that line? Michael

Hi, I'm having some strange issues when using cp in my rsync script. It seems there may be links breaking or something. Before running the actual rsync I run the following command in my script: cp -al /backup/Current /backup/$prevday Then I rsync from the source to /Current So shouldn't all my previous days have hard links back to the original /backup directory? Sometimes the

I can set up and access a dovecot pop3 account using outlook express fine. I can telnet into it fine. However, GFI FaxMaker is failing to log in. I assisted a client in switching his web site, including email from one server (FreeBSD) which was using Cyrus to a Redhat 4.0 server using dovecot version 0.99.11 Here's the listing of dovecot -n: dovecot -n Usage: dovecot [-F] [-c <config

Hi Ankur, > The flags "-view-sched-dags".. described in the doc doesn't seem to work. ( > "llc -help" doesn't list it ). as far as I remember, displaying DAGs during compilation is only enabled in "debug builds" [1] of LLVM. You probably have to re-configure and re-compile LLVM to enable this feature. Best regards, Christoph [1]

Recently I migrated to samba4 in my company. So far so good. debian 6 samba4.1.0pre1 bind9.9.1-P1 (working pretty well. it even updates the reverse zone and no problems at all with the forwarder) ntp-4.2.6p5 All services authenticating with samba4: mail (postfix + dovecot + squirrelmail), jabber (openfire), proxy (squid), even MS Sql server 2000, Net Support Manager and GFI Endpoint Security.

Hola, Deseo simular un modelo logit con interacción, estimar sus coeficientes y comprobar si son o no parecidos al modelo teórico. Con este ejemplo obtengo que los coeficientes estimados no se asemejan mucho a los originales. ¿Se le ocurre a alguien cuál es el motivo de esta discrepancia? ¿y cómo solucionarlo? Muchas gracias Emilio logisticsimulation <- function(n){ dat <-

I'm trying to track down the problem with the assertion failure in SelectionDAGBuilder.cpp. This is the code: *case* *Intrinsic*::gcroot: *if* (GFI) { *const* Value *Alloca = I.getArgOperand(0); *const* Constant *TypeMap = cast<Constant>(I.getArgOperand(1)); * FrameIndexSDNode *FI = cast<FrameIndexSDNode>(getValue(Alloca).getNode());*

Hi Talin, I think that the framework for GC assumes llvm.gcroot to be in the first block. If it is not the case in your example, it will break these assumptions. Nicolas On Sun, Sep 26, 2010 at 1:38 AM, Talin <viridia at gmail.com> wrote: > I'm working on the code to handle GC tracing of "intermediate values" (as > described in the GC doc), and I've run into a

I am trying to understand the SelectionDAG construction from LLVM IR. I have gone through the doc "The LLVM Target-Independent Code Generator" on LLVM site. This gives a great initial overview. However I am unable to catch the actual control flow for the llvm->selectionDag conversion. The flags "-view-sched-dags".. described in the doc doesn't seem to work. ( "llc

Hola, espero ser clara en el mensaje ya que es la primera vez que recurro a este tipo de ayudas, explico mi duda: Tengo un dataset con 4505 observaciones en el que la variable dependiente son presencias (n=97 y clasificadas como 1) y ausencias (n=4408 y clasificadas como 0). Mi primer paso fue realizar un GLM con una muestra compensada de ausencias y presencias para la variable dependiente, es

Hola Lorena: Lo prometido es deuda. Dije que miraría si iba este asunto: ggplot(data = dLSaa, aes(x = factor(AA), y = AD, colour = factor(AA))) + geom_boxplot() + xlab( "AA" ) + ylab( "AD" ) + labs(colour = "Leyenda") + ggtitle(label = "Comparación de AD frente a AA") Y este es el resultado: [image:

Buen día para todos los que ven este correo. En estos días estoy estudiando la potencia de una prueba en inferencia, pero no entiendo bien como correr un codigo que lo haga pertinentemente, el codigo que corro es el siguiente, la idea es que a medida que crece el tamaña muestral pues la potencia de la prueba aumente, pero no se como hacer para que, repita la prueba variando el tamaño de la