| MATLAB Function Reference | ![]() |
ts_min = min(ts)
ts_min = min(ts,'PropertyName1',PropertyValue1,...)
ts_min = min(ts) returns the minimum value in the time-series data. When ts.Data is a vector, ts_min is the minimum value of ts.Data values. When ts.Data is a matrix, ts_min is a row vector containing the minimum value 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, min always operates along the first nonsingleton dimension of ts.Data.
ts_min = min(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.
The following example illustrates how to find the minimum values in multivariate time-series data.
load count.dat
Create a timeseries object with 24 time values.
count_ts = timeseries(count,[1:24],'Name','CountPerSecond')
Find the minimum in each data column for this timeseries object.
min(count_ts)
ans =
7 9 7
The minimum is found independently for each data column in the timeseries object.
iqr (timeseries), max (timeseries), median (timeseries), mean (timeseries), std (timeseries), timeseries, var (timeseries)
![]() | min | MinimizeCommandWindow | ![]() |
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