similar to: lattice: loess smooths based on y-axis values

Hi there, My question is about the 'theta' parameter in specification of a NB GAMM. I have fit a GAM with an optimum structure of: SB.gam4<-gam(count~offset(vol_offset)+ s(Depth_m, by=StnF, bs="cs")+StageF*RegionF, family=negbin(1, link=log), data=Zoop_2011[Zoop_2011$SpeciesF=='SB',]) However, this GAM shows heterogeneity in the

Hi All, Another quick question - I noticed that COZIGAM has been removed from CRAN, and that you are referred to the archive for previous versions (last updated 23 July 2012). Is this package still ok to use? Or is there an alternative which might also fit zero-inflated GAMs? Thanks, Raeanne The Scottish Association for Marine Science (SAMS) is registered in Scotland as a Company Limited by

Greetings everyone, I am running MDS on a very large dataset (12 x 25071 - 12 model runs with 25071 output values each), and also on a very much reduced version of the dataset (randomly select 1000 of the 25071 output values). I would like to look at similarities/dissimilarities between the 12 model runs. When I use metaMDS on the full dataset, I get a warning message: Warning message: In

Hi All, i've problem to understand how to work with R to generate a hierarchical clustering my data are in a csv and looks like : idcode,count,temp,sal,depth_m,subs 16001,136,4.308,32.828,63.46,47 16001,109,4.31,32.829,63.09,49 16001,107,4.302,32.822,62.54,47 16001,87,4.318,32.834,62.54,48 16002,82,4.312,32.832,63.28,49 16002,77,4.325,32.828,65.65,46 16002,77,4.302,32.821,62.36,47

Dear All, I'm confortable with xyplot(...) and panel.lmline(...) statements (at least I thought I did :). I've used the following code to plot the decline in log-abundance of fish larvae (no.larvae) with age (age.cls, 4 to 27 days-old) for specific dates of sampling (day, 9 dates). I further plotted data with different colors and regression lines for ages 5-14 d and 17-23 d in a 7-by-1

I am very new to R and programming and thank you in advance for your patience and help with a complete novice! I am working with a large multivariate data set that has 10 explanatory environmental variables (e.g. temp, depth) and over 60 response variables (each is a separate species). My data frame is set up like the simplified version below: JulianDay Temperature Salinity Depth Copepod

Dear all I have made some lattice graphs (bwplot(dead ~ treat | group,...). 'group' is a factor with three levels (Artemia larvae, Abalone larvae and Abalone spat), and the result is a graph with three panels corresponding to the levels in 'group', ordered in alphabetical order from bottom to top, as expected. How does one re-order the order in which the levels of

Hello r-list members, I've been doing some linear modeling with a dataset structured as follows. Tubes containing 500 larvae of Trichinella each were treated with one of four different temperatures. Each day (or every 10 days depending on treatment group), 3 tubes were selected from each treatment and all the dead larvae were counted. The tubes were discarded. Final larvae counts were

Dear all, How do I make R show the R-squared (deviance explained by the model) in a logistic regression? Below is how I write my syntax. Basically I want to investigate density-dependence in parasitism of larvae. Note that in the end I perform a F-test because the dispersion factor (residual deviance / residual df) is significantly higher than 1. But how do I make R show the

In Dr. Wood's book on GAM, he suggests in section 4.1.6 that it might be useful to shrink a single smooth by adding S=S+epsilon*I to the penalty matrix S. The context was the need to be able to shrink the term to zero if appropriate. I'd like to do this in order to shrink the coefficients towards zero (irrespective of the penalty for "wiggliness") - but not necessarily all the

Background: OS: Linux Ubuntu Dapper R : Version 2.3.1 (2006-06-01) Emacs 21.4.1 ESS Colleagues This is neither a bug report, nor a complaint, so I think this is the appropriate list. I am getting an odd font problem with a pdf generated using pdf(file = "../figures/PCNM.models.larvae.fluor.zoo.stability.2001.and.2002.pdf", title="", family="serif",

I am having difficulty fitting a mgcv::gamm model that includes both a random smooth term (i.e. 'fs' smooth) and autoregressive errors. Standard smooth terms with a factor interaction using the 'by=' option work fine. Both on my actual data and a toy example (below) I am getting the same error so am inclined to wonder if this is either a bug or a model that gamm is simply unable

> Background: > OS: Linux Ubuntu Dapper > release: R 2.3.0 > editor: GNU Emacs 21.4.1 > front-end: ESS 5.2.3 > ----------------------------- > Colleagues > I have two spatial datasets (latitude, longitude, fish eggs) and (latitude, longitude, fish larvae) at the same 280 stations (i.e. 280 cases). I want to determine if the 2 datasets are spatially correlated. In other

I am trying to test out several mgcv::gam models in a scalar-on-function regression analysis. The following is the 'hierarchy' of models I would like to test: (1) Y_i = a + integral[ X_i(t)*Beta(t) dt ] (2) Y_i = a + integral[ F{X_i(t)}*Beta(t) dt ] (3) Y_i = a + integral[ F{X_i(t),t} dt ] equivalents for discrete data might be: 1) Y_i = a + sum_t[ L_t * X_it * Beta_t ] (2) Y_i

I'd like to compare tests based on the mixed model representation of additive models, testing among others y=f(x1)+f(x2) vs y=f(x1)+f(x2)+f(x1,x2) (testing for additivity) In mixed model representation, where X represents the unpenalized part of the spline functions and Z the "wiggly" parts, this would be: y=X%*%beta+ Z_1%*%b_1+ Z_2%*%b_2 vs y=X%*%beta+ Z_1%*%b_1+ Z_2%*%b_2 + Z_12

Background: OS: Linux Mandrake 10.1 release: R 2.0.0 editor: GNU Emacs 21.3.2 front-end: ESS 5.2.3 --------------------------------- Colleagues I have a set of lattice plots, and want to plot 4 of them on the page. I am having trouble with the layout. grid.newpage() pushViewport(viewport(layout = grid.layout(2,2))) pushviewport(viewport(layout.pos.col = 1, layout.pos.row = 1)) working trellis

I'm using the image.plot() function (fields package), but I want to enlarge the characters of the legend (as they are too small to be read in a combined figure), but there is no way I can find a command to do this. I can enlarge the legend bar (with legend.witdh), axis character size (cex.axis) or the total legend size (legend.shrink), but not the character size of the legend characters

Hi, I'm trying to create a plot showing the density distribution of some shipping data. I like the look of violin plots, but my data is not continuous but rather binned and I want to make sure its binned nature (not smooth) is apparent in the final plot. So for example, I have the number of individuals per vessel, but rather than having the actual number of individuals I have data in the

hi! i want to change the "robustness weights" used by loess. these are described on page 316 of chambers and hastie's "statistical models in S" book as r_i = B(e_i,6m) where B is tukey's biweight function, e_i are the residulas, and m is the median average distance from 0 of the residuals. i want to change 6m to, say, 3m. is there a way to do this? i cant

I'm updating the loess routines to allow for, among other things, arbitrary local polynomial degree and number of predictors. For now, I've given the updated package its own namespace. The trouble is, panel.loess still calls the original code in package:stats instead of the new loess package, regardless of whether package:loess or package:lattice comes first in the search list. If I