search for: curvilinear

Hello all: A question from a new user. I have data on a geo-referenced curvilinear grid. This is a grid with 75 rows and 51 columns, is not aligned north-south, and the rows and columns are not straight. (And the coordinates are in meters.) I want to make image plots of this data, but where the grid is deformed according to the correct locations of the grid points, instead of c...

...--", "y-+", "z--"), nticks = 5, ylim = c(0,200)) bbox3d(color = c("black", "white"), lit = F, back = "line") Any ideas/tips on how to do this? thanks in advance, Patrick -- View this message in context: http://r.789695.n4.nabble.com/RGL-3D-curvilinear-shapes-tp4636011.html Sent from the R help mailing list archive at Nabble.com.

...imensions. Given p-dimensional training data containing d groups (the design space), a classification algorithm (classifier) predicts which group new data belongs to. Generally the input to these algorithms is high dimensional, and the boundaries between groups will be high dimensional and perhaps curvilinear or multi-facted. This R package provides methods for visualising the division of space between the groups. More information and a paper describing the ideas can be found at http://had.co.nz/classifly/. Regards, Hadley _______________________________________________ R-packages mailing list R-pac...

...ome and are correlated). Family groups are identified by the variable FAMILY. For each subject multiple measurements are made of the trait of interest (zerotg) over the course of several hours (time). The data within each subject are of course correlated and over time each subject's response is curvilinear. I know how to deal with the within subject correlation using a growth-curve analysis: zerotgQuad0ML.lme <- lme (zerotg ~ time + time^2 + rs2304795 + rs2304795 * time + rs2304795 * time^2, data = GC, random = ~ 1 + time + time^2 | HAPI, na.action = na.omit, m...

adventurous burgundian rook elkhart butterball concave chaplin dustbin trout plane pedestal cinquefoil ely indigene choir curvilinear scald zing bramble braid cobol composition tripartite bust torpedo transverse marvin crestfallen troika molybdate aflame righteous aden diffusive lenin wilcox downright pittsburgh inflammable smear cathy orinoco

Hi everybody, I try to calculate and display the marginal effect(s) in a hierarchical model using lmer. Here is my model: m1<- lmer(vote2011~ Catholic + Attendance+ logthreshold + West + Catholicproportion+ (Catholic * Catholicproportion) + (Attendance*Catholicproportion) + Catholicproportion?+ (Catholic *Catholicproportion?)+ (Attendance* Catholicproportion?) + (1 + Attendance+ Catholic

Hello all, In lme4 if you want to model two non-nested random effects you code it like this: mod1 <- lmer(y~x + (1|randomvar1) + (1|randomvar2)) How would you go about to model something similar in nlme? In my database I have two variables for which I have repeated measures, lets call them "individual" and "year". But none of the "individuals" were measured in

Hello, I am trying to do a logistic regression and have one predictor variable (x) that is ratio and two predictor variables (y and z) that are categorical. These have three levels each which I have called "High", "Medium" and "Low". My question: do I need to use a numerical coding scheme for the categorical variables as required by some statistical software

...) > 35. estimation of NA by predict command (eliza botto) > 36. Re: fill 0-row data.frame with 1 line of NAs (Brian Diggs) > 37. Help with vectors and rollapply (Raghuraman Ramachandran) > 38. Re: multiple comparisons with generalised least squares (Ariel) > 39. RGL 3D curvilinear shapes (PatGauthier) > 40. Re: estimation of NA by predict command (arun) > 41. Re: Count of elements in coulmns of a matrix (arun) > 42. Re: Help with vectors and rollapply (William Dunlap) > 43. Re: Predicted values for zero-inflated Poisson (Laura Lee) > 44. Re: Use...