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Mean of `timeseries`

data

`tsmean = mean(`

specifies additional options when computing the mean using one or more name-value
pair arguments. For example, `ts`

,`Name,Value`

)```
tsmean =
mean(
```

defines -99 as the missing sample quality code, and removes the missing samples
before computing the mean.`ts`

,'Quality',-99,'MissingData','remove')

MATLAB^{®} determines weighting by:

Attaching a weighting to each time value, depending on its order, as follows:

First time point — The duration of the first time interval

`(t(2) - t(1))`

.Time point that is neither the first nor last time point — The duration between the midpoint of the previous time interval to the midpoint of the subsequent time interval

`((t(k + 1) - t(k))/2 + (t(k) - t(k - 1))/2)`

.Last time point — The duration of the last time interval

`(t(end) - t(end - 1))`

.

Normalizing the weighting for each time by dividing each weighting by the mean of all weightings.

**Note**If the

`timeseries`

object is uniformly sampled, then the normalized weighting for each time is 1.0. Therefore, time weighting has no effect.Multiplying the data for each time by its normalized weighting.

`median`

| `std`

| `sum`

| `timeseries`

| `var`