IRIS Toolbox Reference Manual

# Time series objects and functions

Tseries methods:

#### Constructor

- `tseries` - Create new time series (tseries) object.

#### Getting information about tseries objects

- `daily` - Calendar view of a daily tseries object.
- `enddate` - Date of the last available observation in a tseries object.
- `freq` - Frequency of a tseries object.
- `get` - Query tseries object property.
- `isequal` - [Not a public function] Compare two tseries objects.
- `length` - Length of tseries object.
- `ndims` - Number of dimensions in tseries object data.
- `size` - Size of tseries object data.
- `startdate` - Date of the first available observation in a tseries object.
- `yearly` - Display tseries object one full year per row.

#### Referencing tseries objects

- `subsasgn` - Subscripted assignment for tseries objects.
- `subsref` - Subscripted reference function for tseries objects.

#### Maths and statistics functions and operators

Some of the following functions require the Statistics Toolbox.

`+`, `-`, `*`, `\`, `/`, `^`, `&`, `|`, `~`, `==`, `~=`, `>=`, `>`, `<`, `<=`, `abs`, `acos`, `asin`, `atan`, `atan2`, `ceil`, `cos`, `exp`, `fix`, `floor`,`imag`, `isinf`, `isnan`, `log`, `log10`, `real`, `round`, `sin`, `sqrt`, `tan`, `normpdf`, `normcdf`, `prctile`, `lognpdf`, `logncdf`

The behaviour of the following functions depend on the dimension along which they are performed.

Some of the following functions require the Statistics Toolbox.

`all`, `any`, `cumprod`, `cumsum`, `find`, `geomean`, `max`, `mean`, `median`, `min`, `mode`, `nanmean`, `nanstd`, `nansum`, `nanvar`, `prod`, `std`, `sum`, `var`

#### Filters

- `arf` - Run autoregressive function on a tseries object.
- `bpass` - Band-pass filter.
- `bwf` - Butterworth filter with tunes.
- `bwf2` - Swap output arguments of the Butterworth filter with tunes.
- `detrend` - Remove a linear time trend.
- `expsmooth` - Exponential smoothing.
- `hpf` - Hodrick-Prescott filter with tunes (aka LRX filter).
- `hpf2` - Swap output arguments of the Hodrick-Prescott filter with tunes.
- `fft` - Discrete Fourier transform of tseries object.
- `llf` - Local level filter (aka random walk plus white noise) with tunes.
- `llf2` - Swap output arguments of the local linear trend filter with tunes.
- `moving` - Apply function to moving window of observations.
- `trend` - Estimate a time trend.
- `x12` - Access to X12 seasonal adjustment program.

#### Estimation and sample characteristics

Note that most of the sample characteristics are listed above in the Maths and statistics functions and operators section.

- `acf` - Sample autocovariance and autocorrelation functions.
- `hpdi` - Highest probability density interval.
- `chowlin` - Chow-Lin distribution of low-frequency observations over higher-frequency periods.
- `regress` - Ordinary or weighted least-square regression.

#### Visualising tseries objects

- `area` - Area graph for tseries objects.
- `bar` - Bar graph for tseries objects.
- `barcon` - Contribution bar graph for tseries objects.
- `errorbar` - Line plot with error bars.
- `plot` - Line graph for tseries objects.
- `plotcmp` - Comparison graph for two time series.
- `plotpred` - Plot Kalman filter predictions.
- `plotyy` - Line plot function with LHS and RHS axes for time series.
- `scatter` - Scatter graph for tseries objects.
- `spy` - Visualise tseries observations that pass a test.
- `stem` - Plot tseries as discrete sequence data.

#### Manipulating tseries objects

- `empty` - Empty tseries object preserving its size in 2nd and higher dimensions.
- `permute` - Permute dimensions of a tseries object.
- `redate` - Change time dimension of a tseries object.
- `reshape` - Reshape size of time series in 2nd and higher dimensions.
- `resize` - Clip tseries object down to a specified date range.
- `sort` - Sort tseries columns by specified criterion.

#### Converting tseries objects

- `convert` - Convert tseries object to a different frequency.
- `double` - Return tseries observations as double-precision numeric array.
- `doubledata` - Convert tseries observations to double precision.
- `single` - Return tseries observations as single-precision numeric array.
- `singledata` - Convert tseries observations to single precision.

#### Other tseries functions

- `apct` - Annualised percent rate of change.
- `bsxfun` - Standard BSXFUN implemented for tseries objects.
- `cumsumk` - Cumulative sum with a k-period leap.
- `destdise` - Destandardise tseries object by applying specified standard deviation and mean to it.
- `diff` - First difference.
- `interp` - Interpolate missing observations.
- `normalise` - Normalise (or rebase) data to particular date.
- `pct` - Percent rate of change.
- `round` - Round tseries data to specified number of decimals.
- `rmse` - Compute RMSE for given observations and predictions.
- `stdise` - Standardise tseries data by subtracting mean and dividing by std deviation.
- `windex` - Simple weighted or Divisia index.
- `wmean` - Weighted average of time series observations.

#### Getting on-line help on tseries functions

    help tseries
    help tseries/function_name

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