search for: estimats

Hello everyone, I am trying to estimate the parameter b. I have Y and X1 which I know and they are both random. However, I also have X2 which I don't know and is also random. I want to estimat b from the model: Y = b*X1 + ( 1 - b ) * X2 Can anyone offer some suggestions. The values of Y and X1 are both pvalues so they are constrained in (0,1). -- Thanks, Jim. [[alternative HTML version

Hi Stef and Alexey I have read some documents about CBQ algorithm from http://www.icir.org/floyd/cbq.html but still have some question about CBQ in Linux . 1. First estimator can estimate how much bandwidth already USED per class. one estimating algorithm is EWMA (exponential weighted moving average), how about Linux implemenatation about estimator? also do you have link for this algorithm? I

Hello, R experts, Sorry for asking this question again again since I really want a help! I have a two-factor experiment data and like to calculate estimates of interation contrasts say factor A has levels of a1, a2, and B has levels of b1, b2, b3, b4, and b5 with 3 replicates. I am not sure the constrast estimate I got is right using the script below:

Dear everyone, I am doing some work about species richness estimation. Nonparametric estimation (such as Chao1, Jacknife1) can be done just using function "specpool()" and "estimateR()" in package "vegan". The problem is that I can not found any functions for parametric estimation (such as MMMeans, MMruns, Michaelis-Menten). Do you know any function for doing this?

...How do I calculate this confidence interval for glm estimate manually?? for A, I use 0.01093048 + c(-1,1) * 0.006446256 * qt(0.985,df=77) which is a different interval i got from the confint(k.glm,level=0.97) above. To be short, what's the right command to find the confidence interval for glm estimats? How do I verify it manully? Thanks. casper -- View this message in context: http://n4.nabble.com/confint-for-glm-general-linear-model-tp954071p954071.html Sent from the R help mailing list archive at Nabble.com.

Hello, R experts, Sorry for asking this question again since I really want a help! I have a two-factor experiment data and like to calculate estimates of interation contrasts say factor A has levels of a1, a2, and B has levels of b1, b2, b3, b4, and b5 with 3 replicates. I am not sure the constrast estimate I got is right using the script below:

Hello, R experts, I have a two-factor experiment data and like to calculate estimates of interation contrasts say factor A has levels of a1, a2, and B has levels of b1, b2, b3, b4, and b5 with 3 replicates. I am not sure the constrast estimate I got is right using the script below: score<-c(7.2,6.5,6.9,6.4,6.9,6.1,6.9,5.3,7.2,5.7,5.1,5.9,7.6,6.9,6.8,

Hello, R experts, Sorry for asking this question again since I really want a help! I have a two-factor experiment data and like to calculate estimates of interation contrasts say factor A has levels of a1, a2, and B has levels of b1, b2, b3, b4, and b5 with 3 replicates. I am not sure the constrast estimate I got is right using the script below:

Dear All, I am using a specific approach for my master thesis. In essence, a supervised reclassification is used as an intermediate step to find chemical parameters which are able to reclassify defined groups. These variables will be used in a next step where location and scale estimators of the groups are important. Traditionally linear discriminant analysis is used for reclassification which

Hola Jose, si CONCATENAR significa APILAR, es decir, concantenar verticalmente, por decirlo de algun modo, podrias hacerlo con rbind(): nuevovector <- rbind(vector1,vector2) Si ademas quieres que cada valor de los vectores originales sea identificado en el nuevovector, puedes usar: nuevovector <- stack(vector1,vector2) en este ultimo caso se agrega una columna adicional tipo factor, con

por favor como se calculan las probabilidades para conformar el segundo vector SI.Distr, en este ejemplo puse la existente en SARS2003 #Análisis paso a paso rm(list = ls()) #existe información de la incidencia de casos de una enfermedad incidencia <-c (1,0,0,0,0,0,0,0,2,1,1,0,1,2,0,2,0,2,2,2,3, 1, 2, 0,2, 0, 1, 1, 2, 1, 1, 2, 3, 0, 1, 2, 0, 2, 1, 3, 1, 6, 3, 3,7, 4, 4, 3, 6,

Alguien me podría sugerir un paquete en R para generar pronóticos con modelos robusto de series de tiempo.   Saludos Enrique RAMOS [[alternative HTML version deleted]]