SpiceFP (version 0.1.2)

finemeshed2d: finemeshed2d

Description

Function that helps to transform a vector into a matrix (with a fine mesh). In the implementation of the spiceFP approach, it allows to transform matrices of coefficients having different dimensions into matrices of the same dimension in order to perform arithmetic operations. In practice, the matrix to be transformed is associated with a contingency table, which implies numerical variables for which classes have been created.

Usage

finemeshed2d(
  x,
  n.breaks1 = 1000,
  n.breaks2 = 1000,
  round.breaks1 = 9,
  round.breaks2 = 9
)

Value

Returns:

finemeshed.matrix

Matrix of dimension n.breaks2 x n.breaks1. The row and column names of finemeshed.matrix are the breaks created from each variable and the associated n.breaks. Each value of finemeshed.matrix is equal to the value of x indexed by the classes containing the row and column names of finemeshed.matrix

finemeshed.values1

First variable breaks

finemeshed.values2

Second variable breaks

Arguments

x

vector or one column matrix to scale. This vector comes from the vectorization of the matrices to be transformed. x is named using the concatenation of the names of the rows and the names of the columns of the matrix to be transformed, as shown in the example below.

n.breaks1

integer. Number of breaks needed for the first variable. The variable for which classes are in first position when constructing x's names is the first variable.

n.breaks2

integer. Number of breaks needed for the second variable. The variable for which classes are in second position when constructing x's names is the second variable.

round.breaks1

integer. Number of decimals for breaks of the first variable.

round.breaks2

integer. Number of decimals for breaks of the second variable.

Details

This function is designed to return a fine meshed matrix and breaks associated. In order to obtain a fine mesh, a high number of breaks must be fixed.

Examples

set.seed(45)
count_table<- hist_2d(x = rnorm(1000),
                      y = rnorm( 1000,5,0.1),
                      breaks_x = seq(-4, 4, by =1),
                      breaks_y = seq(2, 8, by =1))$Hist.Values

df.x<-as.data.frame.table(count_table)
x<-df.x$Freq
names(x)<-paste0(df.x$Var1,"_",df.x$Var2)

res.fm2d <- finemeshed2d(x,100,100)
dim(res.fm2d$finemeshed.matrix)