# Time Series and Panel Series

`time-series-panel-series.Rd`

*collapse* provides a flexible and powerful set of functions and classes to work with time-dependent data:

`findex_by/iby`

creates an 'indexed_frame': a flexible structure that can be imposed upon any data-frame like object and facilitates**indexed (time-aware) computations on time series and panel data**. Indexed frames are composed of 'indexed_series', which can also be created from vector and matrix-based objects using the`reindex`

function. Further functions`findex/ix`

,`unindex`

,`is_irregular`

and`to_plm`

help operate these classes, check for irregularity, and ensure*plm*compatibility. Methods are defined for various time series, data transformation and data manipulation functions in*collapse*.`timeid`

efficiently converts numeric time sequences, such as 'Date' or 'POSIXct' vectors, to a**time-factor / integer id**, where a unit-step represents the greatest common divisor of the underlying sequence.`flag`

, and the lag- and lead- operators`L`

and`F`

are S3 generics to efficiently compute sequences of**lags and leads**on regular or irregular / unbalanced time series and panel data.Similarly,

`fdiff`

,`fgrowth`

, and the operators`D`

,`Dlog`

and`G`

are S3 generics to efficiently compute sequences of suitably lagged / leaded and iterated**differences, log-differences and growth rates**.`fdiff/D/Dlog`

can also compute**quasi-differences**of the form \(x_t - \rho x_{t-1}\).`fcumsum`

is an S3 generic to efficiently compute**cumulative sums**on time series and panel data. In contrast to`cumsum`

, it can handle missing values and supports both grouped and indexed / ordered computations.`psmat`

is an S3 generic to efficiently convert panel-vectors / 'indexed_series' and data frames / 'indexed_frame's to**panel series matrices and 3D arrays**, respectively (where time, individuals and variables receive different dimensions, allowing for fast indexation, visualization, and computations).`psacf`

,`pspacf`

and`psccf`

are S3 generics to compute estimates of the**auto-, partial auto- and cross- correlation or covariance functions**for panel-vectors / 'indexed_series', and multivariate versions for data frames / 'indexed_frame's.

## Table of Functions

S3 Generic | Methods | Description | ||

`findex_by/iby` , `findex/ix` , `reindex` , `unindex` , `is_irregular` , `to_plm` | For vectors, matrices and data frames / lists. | Fast and flexible time series and panel data classes 'indexed_series' and 'indexed_frame'. | ||

`timeid` | For time sequences represented by integer or double vectors / objects. | Generate integer time-id/factor | ||

`flag/L/F` | `default, matrix, data.frame, pseries, pdata.frame, grouped_df` | Compute (sequences of) lags and leads | ||

`fdiff/D/Dlog` | `default, matrix, data.frame, pseries, pdata.frame, grouped_df` | Compute (sequences of lagged / leaded and iterated) (quasi-)differences or log-differences | ||

`fgrowth/G` | `default, matrix, data.frame, pseries, pdata.frame, grouped_df` | Compute (sequences of lagged / leaded and iterated) growth rates (exact, via log-differencing, or compounded) | ||

`fcumsum` | `default, matrix, data.frame, pseries, pdata.frame, grouped_df` | Compute cumulative sums | ||

`psmat` | `default, pseries, data.frame, pdata.frame` | Convert panel data to matrix / array | ||

`psacf` | `default, pseries, data.frame, pdata.frame` | Compute ACF on panel data | ||

`pspacf` | `default, pseries, data.frame, pdata.frame` | Compute PACF on panel data | ||

`psccf` | `default, pseries, data.frame, pdata.frame` | Compute CCF on panel data |