build.constraints {PortfolioProbe} | R Documentation

## Build Constraints for Optimization

### Description

Builds a bounds object suitable for the input linear constraints, and ensures that the constraints are in a suitable form.

### Usage

    build.constraints(x, bounds = NULL)

### Arguments

`x` | required. Vector, matrix or data frame giving the information about the constraint(s) for each asset. See the Details section for more.
`bounds` | optional matrix of bounds. The rows correspond to the constraints. Rows from this matrix that match constraint names that are created for `x` are put into the output `bounds` matrix.

### Value

a list with the following components:

`lin.constraints` | a matrix or data frame similar to the input `x`. This always has column names so that the constraints can be identified.
`bounds` | a matrix with two columns and as many rows as constraints represented by the input `x`. Numeric columns of `x` embody one constraint. Columns that are factors or character or logical represent as many constraints as there are unique values in the column.

### Details

Numeric linear constraints are created with numeric data. Categorical linear constraints (and count constraints) are created with a factor, character data or logical data.

A data frame is required as the input `x` if more than one type of data is given.

### Revision

This help was last revised 2010 January 02.

### See Also

`constraints.realized`, `trade.optimizer`,

### Examples

    my.sc <- matrix(c("energy", "telecom", "energy", "Germany", "France",
            "France"), nrow=3, ncol=2, dimnames=list(c("Asset 1", "Asset 2",
            "Asset 3"), c("Sector", "Country")))
    my.constr <- build.constraints(my.sc)
    my.constr$bounds[,1] <- c(-.05, -.10, 0, .05)
    my.constr$bounds[,2] <- c(.15, .15, .20, .55)

    random.portfolio(100, prices,
            lin.constraints=my.constr$lin.constraints,
            lin.bounds=my.constr$bounds,
            gross.value=1e6, net.value=c(-1e5, 6e5))

[Package PortfolioProbe version 1.00 Index]