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fBasics

stats-interpLinear

Bivariate Linear Interpolation

Description

Bivariate Linear Interpolation. Two options are available gridded and pointwise interpolation.

Usage

linearInterp(x, y = NULL, z = NULL, gridPoints = 21,
    xo = seq(min(x), max(x), length = gridPoints),
    yo = seq(min(y), max(y), length = gridPoints))
    
linearInterpp(x, y = NULL, z = NULL, xo, yo)

Arguments

x, y, z

for linearInterp the arguments x and y are two numeric vectors of grid pounts, and z is a numeric matrix or any other rectangular object which can be transformed by the function as.matrix into a matrix object. For linearInterpp we consider either three numeric vectors of equal length or if y and z are NULL, a list with entries x, y, z, or named data frame with x in the first, y in the second, and z in the third column.

gridPoints

an integer value specifying the number of grid points in x and y direction.

xo, yo

for linearInterp two numeric vectors of data points spanning the grid, and for linearInterpp two numeric vectors of data points building pairs for pointwise interpolation.

Value

linearInterp

returns a list with at least three entries, x, y and z. Note, that the returned values, can be directly used by the persp and contour 3D plotting methods.

linearInterpp

returns a data.frame with columns "x", "y", and "z".

See Also

Examples

## linearInterp -
   # Linear Interpolation:    
   if (require(akima)) {
     set.seed(1953)
     x = runif(999) - 0.5
     y = runif(999) - 0.5
     z = cos(2*pi*(x^2+y^2))
     ans = linearInterp(x, y, z, gridPoints = 41)
     persp(ans, theta = -40, phi = 30, col = "steelblue",
        xlab = "x", ylab = "y", zlab = "z")
     contour(ans)
   }
fBasics

Rmetrics - Markets and Basic Statistics

v3042.89.1
GPL (>= 2)
Authors
Diethelm Wuertz [aut], Tobias Setz [cre], Yohan Chalabi [ctb] Martin Maechler [ctb]
Initial release
2017-11-12

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