# predict: Predict method for objects of class varest and vec2var In vars: VAR Modelling

## Description

Forecating a VAR object of class ‘`varest`’ or of class ‘`vec2var`’ with confidence bands.

## Usage

 ```1 2 3 4``` ```## S3 method for class 'varest' predict(object, ..., n.ahead = 10, ci = 0.95, dumvar = NULL) ## S3 method for class 'vec2var' predict(object, ..., n.ahead = 10, ci = 0.95, dumvar = NULL) ```

## Arguments

 `object` An object of class ‘`varest`’; generated by `VAR()`, or an object of class ‘`vec2var`’; generated by `vec2var()`. `n.ahead` An integer specifying the number of forecast steps. `ci` The forecast confidence interval `dumvar` Matrix for objects of class ‘`vec2var`’ or ‘`varest`’, if the `dumvar` argument in `ca.jo()` has been used or if the `exogen` argument in `VAR()` has been used, respectively. The matrix should have the same column dimension as in the call to `ca.jo()` or to `VAR()` and row dimension equal to `n.ahead`. `...` Currently not used.

## Details

The `n.ahead` forecasts are computed recursively for the estimated VAR, beginning with h = 1, 2, …, n.ahead:

\bold{y}_{T+1 | T} = A_1 \bold{y}_T + … + A_p \bold{y}_{T+1-p} + C D_{T+1}

The variance-covariance matrix of the forecast errors is a function of Σ_u and Φ_s.

## Value

A list with class attribute ‘`varprd`’ holding the following elements:

 `fcst` A list of matrices per endogenous variable containing the forecasted values with lower and upper bounds as well as the confidence interval. `endog` Matrix of the in-sample endogenous variables. `model` The estimated VAR `object`. `exo.fcst` If applicable provided values of exogenous variables, otherwise `NULL`.

Bernhard Pfaff

## References

Hamilton, J. (1994), Time Series Analysis, Princeton University Press, Princeton.

Lütkepohl, H. (2006), New Introduction to Multiple Time Series Analysis, Springer, New York.

`VAR`, `vec2var`, `plot`, `fanchart`

## Examples

 ```1 2 3``` ```data(Canada) var.2c <- VAR(Canada, p = 2, type = "const") predict(var.2c, n.ahead = 8, ci = 0.95) ```

### Example output

```Loading required package: MASS

Attaching package: 'zoo'

The following objects are masked from 'package:base':

as.Date, as.Date.numeric

\$e
fcst    lower    upper        CI
[1,] 962.6557 961.9446 963.3668 0.7111044
[2,] 963.6538 962.3422 964.9654 1.3116050
[3,] 964.6932 962.8261 966.5603 1.8670903
[4,] 965.6882 963.3092 968.0671 2.3789396
[5,] 966.5814 963.7240 969.4387 2.8573301
[6,] 967.3460 964.0344 970.6576 3.3116112
[7,] 967.9769 964.2302 971.7236 3.7467269
[8,] 968.4827 964.3193 972.6461 4.1633974

\$prod
fcst    lower    upper       CI
[1,] 417.2623 415.9835 418.5411 1.278808
[2,] 417.7410 415.7854 419.6965 1.955532
[3,] 418.2196 415.7674 420.6717 2.452134
[4,] 418.5639 415.6897 421.4380 2.874136
[5,] 418.7644 415.5065 422.0224 3.257935
[6,] 418.8374 415.2253 422.4494 3.612043
[7,] 418.8097 414.8748 422.7446 3.934890
[8,] 418.7110 414.4881 422.9340 4.222973

\$rw
fcst    lower    upper       CI
[1,] 470.2954 468.7660 471.8247 1.529348
[2,] 470.8948 468.8195 472.9701 2.075289
[3,] 471.5360 469.0592 474.0128 2.476757
[4,] 472.2490 469.4525 475.0456 2.796577
[5,] 473.0652 469.9976 476.1329 3.067654
[6,] 473.9943 470.6851 477.3035 3.309184
[7,] 475.0275 471.4966 478.5584 3.530898
[8,] 476.1454 472.4082 479.8825 3.737164

\$U
fcst    lower    upper        CI
[1,] 6.428832 5.880708 6.976957 0.5481244
[2,] 5.903919 5.017510 6.790327 0.8864083
[3,] 5.396177 4.219319 6.573035 1.1768580
[4,] 4.949219 3.518061 6.380377 1.4311576
[5,] 4.595008 2.932516 6.257500 1.6624923
[6,] 4.343933 2.463420 6.224445 1.8805126
[7,] 4.191928 2.102592 6.281265 2.0893366
[8,] 4.126745 1.837864 6.415625 2.2888805
```

vars documentation built on May 1, 2019, 8:23 p.m.