# view_on_marginal_distribution: Views on Marginal Distribution In ffp: Fully Flexible Probabilities for Stress Testing and Portfolio Construction

 view_on_marginal_distribution R Documentation

## Views on Marginal Distribution

### Description

Helper to construct constraints on the marginal distribution.

### Usage

```view_on_marginal_distribution(x, simul, p)

## Default S3 method:
view_on_marginal_distribution(x, simul, p)

## S3 method for class 'matrix'
view_on_marginal_distribution(x, simul, p)

## S3 method for class 'xts'
view_on_marginal_distribution(x, simul, p)

## S3 method for class 'tbl_df'
view_on_marginal_distribution(x, simul, p)
```

### Arguments

 `x` An univariate or a multivariate distribution. `simul` An univariate or multivariate simulated panel. `p` An object of the `ffp` class.

### Details

• `simul` must have the same number of columns than `x`

• `p` should have the same number of rows that `simul`.

### Value

A `list` of the `view` class.

### Examples

```set.seed(1)
library(ggplot2)

# Invariants
ret <- diff(log(EuStockMarkets))
n <- nrow(ret)

#' Prior probability distribution
prior <- rep(1 / n, n)

# Simulated marginals
simul <- bootstrap_scenarios(ret, as_ffp(prior), as.double(n))

views <- view_on_marginal_distribution(x = ret, simul = simul, p = prior)
views

ep <- entropy_pooling(p = prior, Aeq = views\$Aeq, beq = views\$beq, solver = "nlminb")
autoplot(ep)

# location matches
colMeans(simul)
ffp_moments(x = ret, p = ep)\$mu

# dispersion matches
cov(simul)
ffp_moments(x = ret, p = ep)\$sigma
```

ffp documentation built on Sept. 29, 2022, 5:10 p.m.