similar to: Arguments to "personalised" plot()

Hi, I've read up on readBin() and chapter 6 in the R Data Import/Export manual, but I still can't read a binary file. Here is how the creator of the file described the code that would be needed in Fortran: "Every record has a return in fortran. The length of each record is nx*ny*4. To read you would use the following: nlayx = nx*ny*4 do iz=1,nz,4 read(binary file) var(1:nlayx)

I am sure it is just me not understanding how R works, but could somebody explain why curve(cos(x)) works and curve(expression(cos(x)) does not? I have done some investigating and here is what I found. If I comment out the line of curve indicated below, both calls work fine. function (expr, from, to, n = 101, add = FALSE, type = "l", ylab = NULL, log = NULL, xlim =

Hi, I need a help. I am new in R and I need to run a nested anova with fixed and random factors (Mixed Model). I have a design with three factors: Day, Area and Plot and the dependent variable is density. The factors Day and Area are fixed while Plot is random, factor Area is nested in factor Day, and factor Plot is nested in Area. I can do it using aov by: mod1<-aov(density~ day +

Dear List members I am trying to find a way to generate a random point in a circle centred in a geographical location. So far I have used the following formula (see code below): random_x = original_x + radius*cos(angle) random_y = original_y + radius*sin(angle) where radius is a random number between 0 and the radius of the circle and angle is between 0 and 360 degrees The code bellow works

Hi all, I have to calculate an expression using acos -function. A strange result of acos appears *1. case with error* ss <- sin(10.74*pi/180)**2 +(cos(10.74*pi/180)*cos(10.74*pi/180)*cos(0*pi/180)) ss acos(ss) [1] NaN Warning message: NaNs produced in: acos(ss) *2. case without error* ss <- sin(10.7*pi/180)**2 +(cos(10.7*pi/180)*cos(10.7*pi/180)*cos(0*pi/180)) ss acos(ss)

Hi, I'm trying to write a simple function like case1 <- function (m, cov, Q, R) { theta <- (acos(R/sqrt(Q^3))) beta <- (-2)*sqrt(Q)*cos(theta/3)+m[1]/3 rho1 <- (-2)*sqrt(Q)*cos((theta+2*pi)/3)+m[1]/3 rho2 <- (-2)*sqrt(Q)*cos((theta-2*pi)/3)+m[1]/3 stderrb <- deltamethod( ~(-2)*sqrt(Q)*cos(theta/3)+x1/3,m,cov) stderrr1 <- deltamethod(

Hi, I seem to be unable to get a mixed legend that has lines *or* polygons (not both). For example: ppi <- seq(0,2*pi,length.out=21)[-21] frame() plot.window(ylim=c(-5,5),xlim=c(-5,5),asp=1) polygon(cos(ppi)*4+rnorm(20,sd=.2),sin(ppi)*4+rnorm(20,sd=.2), col="green",border=FALSE) polygon(cos(ppi)*2+rnorm(20,sd=.1),sin(ppi)*2+rnorm(20,sd=.1), col="blue",border=FALSE)

Hi, I draw a surface corresponding to bivariate density of independent variables (rho=0) using persp(). Then I add a contour line (i.e., circle in my case) at a particular density. Below is a minimal example of what I have so far. # Bivariate density dnorm2d <- function(x, y, rho = 0) { xoy = (x^2 - 2 * rho * x * y + y^2)/(2 * (1 - rho^2)) density = exp(-xoy)/(2 * pi * sqrt(1 - rho^2))

I'm having trouble understanding the output from as.windrose(). For one thing, data on a boundary between sectors seem to be left out of the counts. I assume that explains the missing point in the output below (angle 45). Shouldn't one side of each sector interval be open, to include values such as my 45 in the example? Also, why does the angle 180 in my input apparently not result in

I want to make a picture of a cos wave grating (pattern of fuzzy stripes). First I try to make a plot of a cos wave: x<-seq(1:100) y<- 10*cos(2*pi*x*3/length(x)+0)+300 plot(x,y) That works fine. 3 cycles of cos wave. Now try for grating. time<-seq(1:100) f<-function(x,time) 10*cos(2*pi*x*3/length(x)+0)+300 z<-outer(x,time,f) image(x,time,z) I get a vertical grating as expected, BUT

Hi, i try sin, cos, and tan. > sapply(c(cos,sin,tan),function(x,y)x(y),1.23e45*pi) [1] 0.5444181 0.8388140 1.5407532 However, *pi results the following > sapply(c(cospi,sinpi,tanpi),function(x,y)x(y),1.23e45) [1] 1 0 0 Please try whether the following becomes all right. diff -ruN R-3.3.2.orig/src/nmath/cospi.c R-3.3.2/src/nmath/cospi.c --- R-3.3.2.orig/src/nmath/cospi.c 2016-09-15

Hi everyone, I am trying to fit a sine function on one year of wind data. I have two questions below. Looking around on the net I managed to get the following: Sine Equation: y = a + b * sin( c + d*x ) b is the amplitude, c is the phase shift, d is something deal with periodicty of data*.* This can be linearised by sin( c+dx ) = cos(c) * sin(dx) + sin(c) * cos(dx). If one calls dx = x1 y

Hello, in a three dimensional coordinate system, I'd like to find all my experimental data points that fall within an ellipsoid around a fixed coordinate. The fixed point is defined by (x.coord.point, y.coord.point, z.coord.point). The coordinates of the ellipsoid are given by the three vectors x,y,z. In a previous version of my code, I simply used a box instead of an ellipsoid to sort

Hi, I'm doing a k-means cluster with 6 clusters and 15 variables. Any suggestions on how to plot the results? I've tried the standard xy plot, but couldn't get much of it. Thansk in advance, Iuri.

Hello, I am a new R user and I am trying to estimate some generalized linear models (glm). I am trying to compare a model with a gaussian distribution and an identity link function, and a poisson model with a log link function. My problem is that while the gaussian model has significantly lower (i.e. "better") AIC (Akaike Information Criterion) most of the coefficients are not

hello everyone, i am getting problems in graph plotting. When i attach file after adding color attributes in my data set. i got problem of "GlobalEnv" and masked the followings. Like this >attach(machm) The following object(s) are masked _by_ '.GlobalEnv': coll, sp The following object(s) are masked from 'mach': angle, area, dis, plot, sp

Hola, ¿qué tal?: Tengo la siguiente duda: Para el caso del Cosinor Simple: Y = M + A * cos(2*pi*t/T + phi) + error Cuando T conocido, podemos asumir: Y = M + beta * X1 + gamma * X2 + error, siendo X1 = cos(2*pi*t/T) y X2 = sin(2*pi*t/T) En este caso (Cosinor simple) el modelado lo llevo a cabo del siguiente modo: lm( y ~ X1 + X2) Para el caso de componentes múltiples: Y = M + ?Aj *

I am trying to calculate coordinate transformations and in the process of debugging my code using debug I found the following Browse[1]> direction[i] [1] -1.570796 Browse[1]> cos(direction[i]) [1] 6.123032e-17 Browse[1]> cos(-1.570796) [1] 3.267949e-07 Browse[1]> direction[i] [1] -1.570796 Browse[1]> cos(direction[i]) [1] 6.123032e-17 Browse[1]> cos(-1.570796) [1] 3.267949e-07

Dear All, Thanks a lot for the useful help again. I manage to get it done up to a point where I think I just need to apply some smoothing/interpolation to get denser points, to make it nice. Basically, I started from Duncen's script to visualize and make the clipping along a plane at a slice. Then I map my data points' values to a color palette and just plot them as points on this plane.

I inherited a function written either for an older version of R or SPlus to draw a brace, "{", in a graph. It uses par("uin") to determine the scaling of the quarter circles that make up segments of the brace, but that setting doesn't exist in current R. I'm guessing that, in the function below, ux, uy can be defined from par("usr") and