similar to: managing data and removing lines

Dear List, i am trying to produce a 3d plot using wireframe using the code: wireframe(Residuals_FD ~ Elevation * Temperature, data = data2, scales = list(arrows = FALSE), drape = TRUE, colorkey = TRUE) As you can see when the code (using the data below) is run the plot area is set-up correctly but the actual surface is missing? Any help would be greatly appreciated. Chris #data Elevation

Dear friends, when i use glm() to fit my data, i use glm(formula = snail ~ vegtype + mhveg + humidity + elevation + soiltem, *family = Gamma(link = inverse),* data =a,)) It shows: error in eval(expr, envir, enclos) : *gamma distribution don't allow negative value*. But i use result<-glm(formula = snail ~ vegtype + mhveg + humidity + elevation + soiltem, family = poisson, data =a) #this

Dear All, I would like to ask clarifications on the gower distnce matrix calculated by the function gdistin the library mvpart. Here is a dummy example: > library(mvpart) Loading required package: survival Loading required package: splines mvpart package loaded: extends rpart to include multivariate and distance-based partitioning > x=matrix(1:6, byrow=T, ncol=2) > x [,1]

Dear R community, I am analyzing plant communities with the function mvpart, using a dissimilarit matrix as input. The matrix is calculated with the funtion gdist. fit <- mvpart(gdist (ba12[,18:29], meth="maximum", full=TRUE, sq=F) ~ beers + slope_dem + elev_dem+ plc_dem + pr_curv+ +curv+max_depth+doc_rocks+ abandon+land_use+ca_old, data=ba12, xv="p") This

Dear all, I'm getting an error in one of the stock examples in the 'mvpart' package. I tried: require(mvpart) data(spider) fit3 <- rpart(gdist(spider[,1:12],meth="bray",full=TRUE,sq=TRUE)~water+twigs+reft+herbs+moss+sand,spider,method="dist") #directly from ?rpart summary(fit3) ...which returned the following: Error in apply(formatg(yval, digits - 3), 1,

Hello I have 2 rows in a matrix and I want to calculate the Gower Distance between the 2 , how can I do it? I searched and found nothing that can help me, and my program doesn't know the gdist function and I couldn't find it on the R help site. Can anyone help me plz Thank u all [[alternative HTML version deleted]]

Hello!!! I have a folder (C:/R/) with matrix files, named by number, i.e. 0.mat, 1.mat,...,1250.mat. In this case, they are 5x5 simetric matrices. I would like to compute a property for each matrix and put calculated values into a data frame for posterior ploting and printing. Below there is an example for 7 matrices (0.mat..6.mat) #define data frame L <- data.frame(frame=numeric(7),

Dear R users, I am reading data from a file where there are some missing that are represented by -9999.00. I am using the command below. =====My original data =========== PARM = TMPC;T12X;T12N;DWPC;PALT;SKNT;DRCT;P24M;CLCL STN YYMMDD/HHMM TMPC T12X T12N DWPC PALT SKNT DRCT P24M CLCL 820420 110429/1200 22.50 -9999.00

Hi all, I would like to know a way of calculating the distance between 2 points when I already have the longitude and latitude of the points. For example : Point 1 : 52? 9'54.00"N 4?25'8.40"E Point 2 : 52?27'46.80"N 4?33'18.00"E Distance between point 1 and point in km .... Is there any functions already available for this ? Any help will be much

Estimada comunidad tengo un problema del que no encuentro datos que me ayuden mucho en la web. Estoy haciendo calculos por grupos con data,table. Tengo un archivo (zp.res) con tres columnas que clasifican los datos (sol, con, dia) y una columna de datos numericos (media), de la siguiente forma: sol con dia media 1: con 0 1 -22.6 2: con 0 1 -36.6 3: con 0 1 -35.6 y

Hi, Suppose I have the following vector (data points): > x [1] 36.0 57.3 73.3 92.0 300.4 80.9 19.8 31.4 85.8 44.9 24.6 48.0 [13] 28.0 38.3 85.2 103.6 154.4 128.5 38.3 72.4 122.7 123.1 41.8 21.7 [25] 143.6 120.2 46.6 29.2 44.8 25.0 57.3 96.4 29.4 62.9 66.4 30.0 [37] 24.1 14.8 56.6 102.4 117.5 90.4 37.2 79.6 27.8 17.1 26.6 16.3 [49] 41.4 48.9 24.1

Hi R users, I'm here trying to understand correlated residuals in nonlinear estimation. I'm reading/studying the book Bates, D. M. and D. G. Watts, (1988), /Nonlinear regression analysis and its applications/, Wiley, NY. pages 92-94, trying to reproduce the figures and to find out the code in R to perform the necessary calculations. I also consulted Pinheiro and Bates, but without

Hola: ¿Existe alguna forma de obtener el valor numérico de los intervalos de confianza en una autocorrelación? O, por el contrario, ¿tengo que calcularlos «a mano»? (Llevo ya un rato buscando y nada.) Gracias por adelantado. Salud y Revolución. Lobo. -- Libertad es poder elegir en cualquier momento. Ahora yo elijo GNU/Linux, para no atar mis manos con las cadenas del soft propietario.

I'm interested in clustering my data using the Gower Similarity Coefficient, and I was wondering if R is capable of using that metric Timothy Rye [[alternative HTML version deleted]]

On 5 March 2018 at 03:13, Sparks, John wrote: | library(quantmod) | #in fairness, I did not include this last time and my example was therefore not reproducible. Apologies to Bert and everyone else #for not following the posting guidelines. | aapl_total<-getOptionChain("AAPL", NULL)> | | How could I then get the subset of the entire list which only has expiry dates in 2019, or

R-gurus... I've got a 5 column dataframe where I'd like to plot each ID's "b" against "c" with "b" in ascending order (within the same ID). How do I sort "b" so that the other variables are altered equally? ID a b c d 101 1 240 26.7 21.85 101 2 335 21.8 21.85 101 3 1387 26.6 21.85 101 4 877 24.1 21.85

I've got a list of 5 matrices that are each 5 x 6. I'd like to end up with a 5 x 6 matrix that contains the mean value of the 5 original matrices. I can do this by brute force, but there must be a better way than making each matrix into a vector and then remaking a matrix thanks very much for any help david freedman ll=list(structure(c(9.7, 17.6, 20.8, 24.1, 33.8, 14.5, 25.7, 29.8,

Some day I may figure out how ggplot2 works. I am trying to plot 5 columns of data on a graph (similar to a simple matplot) =========================================================================== library(ggplot2) bmi <- structure(list(pct = 2:21, P10 = c(14.6, 14.5, 14.2, 13.9, 13.7, 13.7, 13.9, 14.2, 14.5, 14.8, 15.3, 15.9, 16.6, 17.2, 17.8, 18.1, 18.3, 18.4, 18.5, 18.6), P25 =

Hello, I have noticed that the memory usage inside an R session increases as more and more objects with unique names are created, even after they are removed. Here is a small reproducible example: > gc() used (Mb) gc trigger (Mb) max used (Mb) Ncells 531720 14.2 899071 24.1 818163 21.9 Vcells 247949 1.9 786432 6.0 641735 4.9 > > for (i in 1:100000) { + name <-

It looks like fixed width. I just used the last position of each field to get the size and used the 'readr' package; > input <- "And XVIII 000214.5+450520 0.69 17 9 0.00 -8.7 26.8 6.44 6.78 < 6.65 -44 0.5 MESSIER031 0.6 1.54 + PAndAS-03 000356.4+405319 0.10 17 0.00 -3.6 27.8 4.38 2.8 MESSIER031