search for: basal

...ference in means as the response and treating within-means residuals as a random effect. I have a dataframe (my own, a snippet of which is given below) that is composed of observations of pollen viability in flowers along tree branches. Flowers (1 to 3 per position) were collected from apical and basal positions along the same branch, and I'm predicting that the within-branch difference between the mean viabilities at each position is a function of the distance separating the positions, with tree as a random effect. A collection of observations for a single branch is: tree branch...

I have a data frame with two columns, one of which is a factor (Species) and the other is numeric (BA, which stands for basal area). Here's a sample: Species BA ACSA 55.7632696 FRAM 122.9933524 ACSA 67.54424205 ACSA 89.22123136 ACSA 82.46680716 ACSA 22.46238747 ACSA 19.94911335 ACSA 20.42035225 ACSA 19.00663555 ACSA 21.67698931 ACSA 57.80530483 ACSA 30.31636911 Dead 43.98229715 Dead 40.21238597 Dead 16.49336143 D...

...ce them for new F, p, R2 and parameters using lme and nlme as random effects. I am studying distribution patterns of 50 tree species along a gradient. That gradient was sampled through 27 transects, with 10 plots within each transect. For each plot I have data on presence/absence, abundance and basal area of the species. I also have data for 4 environmental variables related to water availability (soil water retention capacity, slope, insolation, altitude) and X and Y coordinates for each plot. I explored wether the relationship between any of the response variables (presence/absence, abund...

...) and I would like to "cbind()" the lists together to create a "cross tab" report or simply bind them together somehow the function returns a list that looks like the following: > all$BM $species [1] "BM" $vbar.nobs [1] 3 $vbar.sum [1] 54.05435 $count.nobs [1] 20 $basal.area [1] 26 $expf [1] 5.339182 > so there are different variable types in the list (meaning I can't use cbind?) to create a table with more than one column for stringing together multiple species. I tried to use rbind and got similar results. Tried unlist, but the values get cast into stri...

Hi everyone, I have been working some days in a nested loop in R but I can't find the solution. I have a data.frame with an unique ID for individuals and unique ID for different stands, for each indiviadual I have a dbh record and a SBA (stand basal area) field. Pma<-rep (1:40) P<-seq(1,4, 1) Plot<-rep(P,10) dbh2<-rnorm(40, mean=200, sd=5) SBA2<-rnorm(40, mean=10, sd=1) As I want to calculate the basal area of larger trees in each stand (i.e., the compare tree to tree the dbh and for each individual sum the stand basal area of...

Dear List, I'm an [R] novice starting analysis of an ecological dataset containing the basal areas of different tree species in a number of research plots. Example data follow: > Trees<-data.frame(SppID=as.factor(c(rep('QUEELL',2), rep('QUEALB',3), 'CORAME', 'ACENEG', 'TILAME')), BA=c(907.9, 1104.4, 113.0, 143.1, 452.3, 638.7, 791.7, 804.3), P...

Here's another interesting problem: if you recall I have a data frame (LCvars1) that consists of about 1500 cases (rows) of data from kids who took a test of listening comprehension. The columns are their scores (1 = correct, 0 = incorrect, . = missing) on 140 test items. The items are numbered sequentially and are ordered by increasing difficulty as you go from left to right across the

...ach category to have a unique colour, however, with the coding I have (below), the colour black is repeated for two of my plot types. Does anyone know a quick way to get 9 unique colours?? Coding: plotba = plot (predictedba ~ actualba, col=as.numeric(ecosite), pch=19, cex=1.5, ylab="Predicted Basal Area (m2/ha-1)", xlab="Actual Basal Area (m2/ha-1)") Thanks! Here's what it looks like currently: http://r.789695.n4.nabble.com/file/n4078889/predicted_height.jpeg -- View this message in context: http://r.789695.n4.nabble.com/Getting-unique-colours-tp4078889p4078889.html Se...

Dear R-users, I want to fit a linear model with Y as response variable and X a categorical variable (with 4 categories), with the aim of comparing the basal category of X (category=1) with category 4. Unfortunately, there is another categorical variable with 2 categories which interact with x and I have to include it, so my model is s "reg3: Y=x*x3". Using fit.contrast to make the contrast (category 1 vs category 4) with options(contrasts=c(...

...some reason R doesn't recognize the "hat" symbol. plot(1,1,xlab="ligth intensity (PAR)",ylab=expression("mass Pteridium rhizomes" (gr/0.25m^2))) A very similiar scriptline does not give any problem at all: plot(1,1,xlab=expression("balsa plot basal area" (m^2/ha)),ylab="light intensity (PAR)") Someone? _________________________________________________________________ s. It's easy! aspx&mkt=en-us

...sp = rep(rep(leg.txt, each = 3), times = 7) ga = runif(147, 0, 20) datnew.lo = data.frame(site,sp,ga) # Now make the plot: boxplot(ga~sp*site,data=datnew.lo, range = 1, col = colors, ylim = c(0,30), xaxt = "n", xlab = "Site", ylab = "Basal Area Growth Increment", main = "Basal Area Growth Increment by Site and Species") axis(1, at = c(4,11,18,25,32,39,46), labels = site.txt, ) abline(v = 7.5, lty = 3) abline(v = 14.5, lty = 3) abline(v = 21.5, lty = 3) abline(v = 28.5, lty = 3) abline(v = 35.5, lty =...

Hi all, I am using the vegan package to run a prcincipal components analysis on forest structural variables (tree density, basal area, average height, regeneration density) in R. However, I could not find out how to extract factor loadings (correlations of each variable with each pca axis), as is straightforwar in princomp. Do anyone know how to do that? Moreover, do anyone knows a function r package that produce...

Buenas. Abajo pongo la salida de un modelo de cox , dónde he estratificado por una variable de país (Countryb) y por otra (Q6). Además hay interacción entre la variable mobilityPDurG2 (es una variable 0,1, y 0 es la categoría de referencia) país. La categoría de referencia para país es "united kingdom". Mi duda surge si quiero calcular el hazard ratio para los que tienen un 1

Dear All, here a problem I think many of you can solve in few minutes. I have a dataframe which contains values of plot id, diameters, heigths and basal area of trees, thus columns names are: id | dbh | h | g head(ipso, n=10) id dbh h g 1 FPE0164 36 13.62 0.10178760 2 FPE0164 31 12.70 0.07547676 21 FPE1127 57 18.85 0.25517586 13 FPE1127 39 15.54 0.11945906 12 FPE1127 34 14.78 0.09079203 6 FPE1127 32 15.12 0.08042477 5...

Dear All, I am Ricky Jacob, a project Student from India who is working on Forest Inventories. Input data: Plot(area = .1 ha) data having the following information: 1) Basal Area 2)Tree Density 3)Volume So I am applying this information to the corresponding pixels in the satellite imagery of the study area. I also have given the same values to a 3x3 window around that pixel. Inventory is taken compartmentwise and so this information of all the plots in a compartment i...

...gh will be sent for CT (computed tomography). Using a risk threshold of 0.025 (2.5%), turn the result into a decision rule for use of CT. This is what I have so far: > names(head.injury) [1] "age.65" "amnesia.before" [3] "basal.skull.fracture" "GCS.decrease" [5] "GCS.13" "GCS.15.2hours" [7] "high.risk" "loss.of.consciousness" [9] "open.skull.fra...

Dear All, I am not able to run the random forest with my dataset.. X<- 280 records with satellite data(28 columns) - B1min, b1max, b1std etc.. y<- 280 records with 3 columns - TotBasal Area, Stem density and Volume yref <- y[1:230,] #Keeping 1st 230 records as reference records want to set 0 to y values for records 231 to 280.. yimp <- y[231:280,] #records for which we want to impute the basal area, stem density and volume mal1 <- yai(x=x, y=yref, method="...

Hi I am conducting 2-sample Kolmogorov Smirnov tests for my Masters project to determine if two independant tree populations have the same size-class distribution or not. The trees have been placed into size-class categories based on their basal diameters. Once I started running the stats on my data, I got confused with the results. Just to show an example of what I was testing I ran stats comparing population1 to population 2. and then comparing population 3 to population 2. Popn1 Popn2 Popn3 880 769 0 34 40 19 10 24 19 2 2 8 2 2 3...

...I can use it in further calculations. For example, I would like to aggregate the expf for the data.frame by sp (character) and dbh (double d=rounded to integer) using the command: > st2 <- aggregate( ntrs$expf, by=list(sp=ntrs$sp,dbh=ntrs$dbh), sum ) > st2$expf <- st2$x / 20 > st2$basal.area <- st2$dbh^2 * st2$expf Warning message: "^" not meaningful for factors in: Ops.factor(st2$dbh, 2) > attributes(st2$dbh) tell me the class is a factor. I would like to values to remain AsIs but cannot seem to figure out how to tell aggregate how to do that, or even handle the...

...enough but to which I cannot find an answer. I am interested in developing a predictive model relating some measure of a tree's stem to the total leaf area (TLA) of the tree. Predictor variables might include, for example, the total cross-sectional area of the tree (commonly referred to as basal area) or the amount of sapwood area (SA) (which represents the amount of wood involved in active transport of water up the tree to the leaves). A variety of people have developed these models for a variety of tree species in a variety of places around the world. Perhaps not surprisingly, differ...