| Mathematial C functions {RandomFields} | R Documentation |
The functions provide mathematical c functions as RMmodels
RFcalc(model) R.minus(a, b, factor) R.plus(a, b, factor) R.div(a, b, factor) R.mult(a, b, factor) R.const(a) R.c(a, b, c, d, e, f, g, h, i, j, factor) R.p(proj, new, factor) R.is(a, is, b) R.lon() R.lat() R.acos(a) asin(x) R.asin(a) atan(x) R.atan(a) atan2(y, x) R.atan2(a, b) cos(x) R.cos(a) sin(x) R.sin(a) tan(x) R.tan(a) acosh(x) R.acosh(a) asinh(x) R.asinh(a) atanh(x) R.atanh(a) cosh(x) R.cosh(a) sinh(x) R.sinh(a) tanh(x) R.tanh(a) exp(x) R.exp(a) log(x) R.log(a) expm1(x) R.expm1(a) log1p(x) R.log1p(a) logb(x) R.logb(a) R.exp2(a) log2(x) R.log2(a) R.pow(a, b) sqrt(x) R.sqrt(a) R.hypot(a, b) R.cbrt(a) R.ceil(a) abs(x) R.fabs(a) floor(x) R.floor(a) R.fmod(a, b) round(x, ...) R.round(a) trunc(x) R.trunc(a) R.erf(a) R.erfc(a) gamma(x) R.gamma(a) lgamma(x) R.lgamma(a) R.remainder(a, b) R.fdim(a, b) max(...) R.fmax(a, b) min(...) R.fmin(a, b)
model |
object of class |
x,y,a, b, c, d, e, f, g, h, i, j, ... |
constant or object of class |
is |
one of |
factor |
constant factor multiplied with the function. This is useful when linear models are built |
proj |
selection of a component of the vector giving the location. Default value is 1. |
new |
coordinate system or other
|
adds two values
substracts two values
multiplies two values
devides two values
defines a constant
builds a vector
evaluates equalities and inequalities;
note that TRUE is returned if the equality or
inequality holds up to a tolerance given by
RFoptions()$nugget$tol
takes a component out of the vector giving the location
longitudinal and latitudinal coordinate, given in the spherical system, i.e. in radians. (earth system is in degrees).
For the remaining models see the corresponding C functions for their return value. (For any ‘R.model’ type ‘man model’ under Linux.)
Formally, the functions return an object of class
RMmodel, except for
RFcalc that returns a scalar.
Neither vectors nor parentheses are allowed.
The function RFcalc is intended for simple calculations only
and it is not excessively tested. Especially, binary
operators should be used with caution.
Note that all the functions here are NOT recognized as being
positive definite (or negative definite), e.g. cos in
R^1:
please use the functions given in RMmodels
for definite functions (for cos see RMbessel)
Using uncapsulated substraction to build up a covariance
function is ambiguous, see the example in RMtrend
Martin Schlather, schlather@math.uni-mannheim.de
RFoptions(seed=0) ## *ANY* simulation will have the random seed 0; set ## RFoptions(seed=NA) to make them all random again ## simple calculation RFcalc(3 + R.sin(pi/4)) ## calculation performed on a field RFfctn(R.p(1) + R.p(2), 1:3, 1:3) RFfctn(10 + R.p(2), 1:3, 1:3) ## calculate the distances between two vectors print(RFfctn(R.p(new="iso"), 1:10, 1:10)) ## simulation of a non-stationary field where ## anisotropy by a transform the coordinates (x_1^2, x_2^1.5) x <- seq(0.1, 6, 0.12) Aniso <- R.c(R.p(1)^2, R.p(2)^1.5) z <- RFsimulate(RMexp(Aniso=Aniso), x, x) ## calculating norms can be abbreviated: x <- seq(-5, 5, 5) #0.1) z2 <- RFsimulate(RMexp() + -40 + exp(0.5 * R.p(new="isotropic")), x, x) z1 <- RFsimulate(RMexp() + -40 + exp(0.5 * sqrt(R.p(1)^2 + R.p(2)^2)), x, x) stopifnot(all.equal(z1, z2)) plot(z1)