Time Series

Data vectors sampled over time

Time series represent the time-evolution of a dynamic population or process. They are used to identify, model, and forecast patterns and behaviors in data that is sampled over discrete time intervals.

Timetables are recommended over timeseries objects for this type of data. Timetables can store time-stamped data of varying types and have a broad set of supporting functions to align, combine, and perform calculations. To get started with timetables, see Create Timetables.

Functions

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Create, Modify, and Plot

`timeseries`	Create `timeseries` object
`timeseries2timetable`	Convert `timeseries` objects to timetable (Since R2021a)
`resample`	Resample time vector in `timeseries` or `tscollection`
`synchronize`	Synchronize and resample two `timeseries` objects using common time vector
`detrend`	Subtract mean or best-fit line from `timeseries` object
`filter`	Modify frequency content of `timeseries` objects
`idealfilter`	`timeseries` ideal filter
`plot`	Plot `timeseries`
`append`	Concatenate `timeseries` objects in time
`addsample`	Add data sample to `timeseries` object
`delsample`	Remove sample from `timeseries` object
`setabstime`	Set `timeseries` or `tscollection` times as date character vectors
`setinterpmethod`	Set default interpolation method for `timeseries` object
`setuniformtime`	Modify uniform `timeseries` time vector

Query

`getsamples`	Subset of `timeseries`
`getsampleusingtime`	Subset of `timeseries` or `tscollection` data
`getdatasamples`	Access `timeseries` data samples
`getdatasamplesize`	`timeseries` data sample size
`getabstime`	Convert `timeseries` or `tscollection` time vector to cell array
`getinterpmethod`	`timeseries` interpolation method
`getqualitydesc`	`timeseries` data quality

Descriptive Statistics

`iqr`	Interquartile range of `timeseries` data
`max`	Maximum of `timeseries` data
`mean`	Mean of `timeseries` data
`median`	Median of `timeseries` data
`min`	Minimum of `timeseries` data
`std`	Standard deviation of `timeseries` data
`sum`	Sum of `timeseries` data
`var`	Variance of `timeseries` data

Collections

`tscollection`	Create `tscollection` object
`addts`	Add `timeseries` to `tscollection`
`removets`	Remove `timeseries` from `tscollection`
`addsampletocollection`	Add sample to `tscollection`
`delsamplefromcollection`	Delete sample from `tscollection`
`gettimeseriesnames`	Names of `timeseries` in `tscollection`
`settimeseriesnames`	Rename `timeseries` in `tscollection`

Events

`tsdata.event`	Create `tsdata.event` object
`addevent`	Add event to `timeseries`
`delevent`	Remove event from `timeseries`
`findEvent`	Query `tsdata.event` by name
`getTimeStr`	Query `tsdata.event` times
`gettsafteratevent`	Create `timeseries` at or after event
`gettsafterevent`	Create `timeseries` after event
`gettsatevent`	Create `timeseries` at event
`gettsbeforeatevent`	Create `timeseries` at or before event
`gettsbeforeevent`	Create `timeseries` before event
`gettsbetweenevents`	Create `timeseries` between events

Topics

Time Series Objects and Collections
There are two types of time series objects in MATLAB^®, a timeseries object and a tscollection object.

Related Information

Timetables