# HRLambda: Parameter matrix of a Huesler-Reiss distribution In gremes: Estimation of Tail Dependence in Graphical Models

 HRLambda R Documentation

## Parameter matrix of a Huesler-Reiss distribution

### Description

It creates the parameter matrix Lambda of the limiting max-stable Huesler-Reiss distribution which is an attractor of a graphical model with respect to some block graph and whose distribution is composed cliquewise from Huesler-Reiss distributions. See Vignette "Introduction" too. The entry lambda_ij is the sum of the edge weights on the shortest path between node i and node j in the block graph. The matrix Lambda can be used to generate observations from that max-stable Huesler-Reiss distribution.

### Usage

```HRLambda(obj, ...)

## S3 method for class 'HRMBG'
HRLambda(obj, ...)
```

### Arguments

 `obj` is an object of class `HRMBG` with non-zero edge weights. `...` additional arguments

### Value

A symmetric matrix whose entry lambda_ij is the sum of the edge weights on the shortest path between node i and node j.

### Examples

```g<- graph(c(1,3,1,2,2,3,
3,4,4,5,5,3,
3,7,3,6,6,7), directed=FALSE)
g<- set.vertex.attribute(g, "name", V(g), c("a", "b", "c", "d", "e", "f", "g"))
# all deltas are squares already
C1<- c(0.2, 0.8, 0.6)   # d_13^2, d_12^2, d_23^2
C2<- c(0.3, 0.5, 0.1)   # d_34^2, d_45^2, d_35^2
C3<- c(0.4, 0.05, 0.25) # d_37^2, d_36^2, d_67^2
hrmbgobj<- HRMBG(g)
hrmbgobj<- setParams(hrmbgobj, c(C1, C2, C3))
hrmlam<- HRLambda(hrmbgobj)
```

gremes documentation built on Feb. 16, 2023, 8:06 p.m.