degrossData {degross}

Creates a degrossData.object from the observed tabulated frequencies and central moments.

Description

Creates a degrossData.object from the observed tabulated frequencies and central moments.

Usage

degrossData(Big.bins, freq.j, m.j, I=300, K=25)

Arguments

Big.bins

Vector of length J+1 with the limits of the J big bins containing the data used to produce the tabulated statistics.

freq.j

The number of data observed within each big bin.

m.j

A matrix of dim J by 4 giving the first 4 sample central moments within each of the J big bins.

I

The number of small bins used for quadrature during the normalization of the density during its estimation. Default: 300.

K

The desired number of B-splines in the basis used for density estimation. Default= 25.

Value

A degrossData.object, i.e. a list containing:

• small.bins : ⁠ ⁠a vector of length I+1 with the small bin limits.

• ui : ⁠ ⁠the I midpoints of the small bins.

• delta : ⁠ ⁠width of the small bins.

• I : ⁠ ⁠the number of small bins.

• B.i : ⁠ ⁠a matrix of dim I by K with the B-spline basis evaluated at the small bin midpoints.

• K : ⁠ ⁠number of B-splines in the basis.

• knots : ⁠ ⁠equidistant knots supporting the B-splines basis.

• Big.bins : ⁠ ⁠vector of length J+1 with the limits of the J big bins containing the data used to produce the tabulated statistics.

• freq.j : ⁠ ⁠the number of data observed within each big bin.

• m.j : ⁠ ⁠a matrix of dim J by 4 giving the first 4 sample central moments within each big bin.

• J : ⁠ ⁠the number of big bins.

• small.to.big : ⁠ ⁠a vector of length I indicating to what big bin each element of ui belongs.

Author(s)

Philippe Lambert [e-mail]

References

Lambert, P. (2021) Moment-based density and risk estimation from grouped summary statistics. arXiv:2107.03883.

See Also

print.degrossData, degross.

Examples

sim = simDegrossData(n=3500, plotting=TRUE)
obj.data = degrossData(Big.bins=sim$Big.bins, freq.j=sim$freq.j, m.j=sim$m.j)
print(obj.data)