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std (timeseries) - Standard deviation of `timeseries` data

Syntax

ts_std = std(ts) ts_std = std(ts,'PropertyName1',PropertyValue1,...)

Description

ts_std = std(ts) returns the standard deviation of the time-series data. When ts.Data is a vector, ts_std is the standard deviation of ts.Data values. When ts.Data is a matrix, ts_std is the standard deviation of each column of ts.Data (when IsTimeFirst is true and the first dimension of ts is aligned with time). For the N-dimensional ts.Data array, std always operates along the first nonsingleton dimension of ts.Data.

ts_std = std(ts,'PropertyName1',PropertyValue1,...) specifies the following optional input arguments:

'MissingData' property has two possible values, 'remove' (default) or 'interpolate', indicating how to treat missing data during the calculation.
'Quality' values are specified by a vector of integers, indicating which quality codes represent missing samples (for vector data) or missing observations (for data arrays with two or more dimensions).
'Weighting' property has two possible values, 'none' (default) or 'time'.
When you specify 'time', larger time values correspond to larger weights.

Examples

Load a 24-by-3 data array.
```
load count.dat
```

Create a timeseries object with 24 time values.

count_ts = timeseries(count,1:24,'Name','CountPerSecond')

Calculate the standard deviation of each data column for this timeseries object.
```
std(count_ts)

ans =

   25.3703   41.4057   68.0281
```

The standard deviation is calculated independently for each data column in the timeseries object.

std (timeseries) - Standard deviation of `timeseries` data

Syntax

Description

Examples

See Also

Recommended Products

std (timeseries) - Standard deviation of timeseries data

Syntax

Description

Examples

See Also

Recommended Products

std (timeseries) - Standard deviation of `timeseries` data