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Convolution with combination of dimensions

Source: R/convolution_comb.R
CONVOLUTION_comb.Rd

In case of different dimensions of the distribution this function perform the operation on the combination of the distributions of both distribution.

Usage

new_CONVOLUTION_comb(dist1, dist2, op, p_dimnames)

new_SUM_comb(dist1, dist2)

new_SUBTRACTION_comb(dist1, dist2)

new_MULTIPLICATION_comb(dist1, dist2)

new_DIVISION_comb(dist1, dist2)

Arguments

dist1

an object of class DISTRIBUTION

dist2

and object of class DISTRIBUTION

op

one of `+`,`-`,`*`,`/`

p_dimnames

a character vector with the name of the dimensions. If missing the combination of the individual dimensions will be used

Value

an object of class DISTRIBUTION

Details

If distribution A have dimensions a and b and distribution B have dimensions b and c, the A + B would produce a distribution with dimensions a_b,a_c,b_b, b_c

Functions

  • new_SUM_comb(): Sum of distributions

  • new_SUBTRACTION_comb(): Subtraction of distributions

  • new_MULTIPLICATION_comb(): Multiplication of distributions

  • new_DIVISION_comb(): Division of distributions

Note

In case of the same dimensions, only the first combination is taken

Author

John J. Aponte

Examples

x1 <- new_MULTINORMAL(c(0,1), matrix(c(1,0.5,0.5,1),ncol=2), p_dimnames = c("A","B"))
x2 <- new_MULTINORMAL(c(10,1), matrix(c(1,0.4,0.4,1),ncol=2), p_dimnames = c("B","C"))
new_CONVOLUTION_comb(x1,x2, `+`)
#>   distribution A_B B_B A_C B_C
#> 1  CONVOLUTION  10  11   1   2
new_SUM_comb(x1,x2)
#>   distribution A_B B_B A_C B_C
#> 1  CONVOLUTION  10  11   1   2
new_SUBTRACTION_comb(x1,x2)
#>   distribution A_B B_B A_C B_C
#> 1  CONVOLUTION -10  -9  -1   0
new_MULTIPLICATION_comb(x1,x2)
#>   distribution A_B B_B A_C B_C
#> 1  CONVOLUTION   0  10   0   1
new_DIVISION_comb(x1,x2)
#>   distribution A_B B_B A_C B_C
#> 1  CONVOLUTION   0 0.1   0   1