Known {demest} | R Documentation

## Specify a prior where the mean varies but is treated as known.

### Description

Specify a 'Known' prior. The prior comes in two forms. With the first form, the corresponding main effect or interaction equals the mean exactly, `parameter[j] = mean[j]`. With the second form, `parameter[j] ~ N(mean[j], sd[j])`. The second form is obtained by supplying a `sd` argument to function `Known`.

### Usage

    Known(mean, sd = 0)

### Arguments

`mean` | The mean of the prior distribution. An object of class `Values`.
`sd` | The standard deviation of the prior distribution. If omitted, it is assumed to be 0. `sd` can be an object of class `Values`, or it can be a single number, in which case it is applied to all elements of `mean`.

### Details

Internally, the `mean` and `sd` arguments are permuted and subsetted to make them compatible with the corresponding main effect or interaction. Thus, for example, if `mean` has values for regions `A`, `B`, and `C`, but data `y` only includes regions `A` and `B`, then `C` is silently ignored.

The original `mean` and `sd` arguments are, however, stored, and can be used for prediction. For example, we might supply a `mean` argument with values for years 2005, 2010, 2015, 2020, and 2025, then call `estimateModel` with data for 2005, 2010, and 2015, and finally call `predictModel` to obtain forecasts for 2020 and 2025.

### Value

An object of class `SpecKnown`.

### See Also

`ExchFixed` creates a normal prior centered at 0.

### Examples

    mean <- ValuesOne(c(0.1, 0.2, 0.3),
                      labels = c("A", "B", "C"),
                      name = "region")
    sd <- ValuesOne(c(0.02, 0.03, 0.02),
                      labels = c("A", "B", "C"),
                      name = "region")
    ## No uncertainty
    Known(mean)

    ## Some uncertainty
    Known(mean = mean, sd = sd)

    ## Single standard deviation
    Known(mean = mean, sd = 0.05)

[Package demest version 0.0.0.3.1 Index]