gives {{t1,f[t1,x1]},{t2,f[t2,x2]},} for the time series tseries.

gives {{t1,f[t1,x1,a1,b1,]},{t2,f[t2,x2,a2,b2,]},} for the time series tseries.

# Examples

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## Basic Examples(2)

Apply a function f to the times and values in a time series:

Create a series with increasing variance as a function of time:

## Scope(7)

### Basic Uses(2)

Set a value at time 3 to 0:

Add time-dependent noise to a vector-valued signal:

### Data Types(5)

Apply a function f to a list of time-value pairs:

Set the values for times greater than 3 in TimeSeries to 1:

Visualize TemporalData for integer times:

Set the middle 50 values of EventSeries to 0:

Modify the values of a time series involving quantities:

Modify the values for times greater than 2:

## Applications(5)

### Inflation(1)

The following are spot oil prices from 1970 to 2010. This data is not corrected for inflation:

The consumer price index (CPI) is often used to correct historical prices for inflation:

Adjusted prices for inflation using the most recent value of the CPI:

Find the adjusted oil price on March 5, 2001:

### Weather(1)

The following are monthly average temperatures for a Missouri city over a three-year period. Separate the seasonal and nonseasonal components of this data:

Fit a model for the seasonal component:

Use the model to obtain the nonseasonal component:

Combining the components yields the original data:

### Simulation(1)

Use TimeSeriesMapThread to simulate a transformed random process:

Simulate WienerProcess:

Apply transformation to the random sample to obtain Brownian bridge:

Compare to the corresponding BrownianBridgeProcess:

### GDP(1)

Study the discrepancy in the estimate of GDP for Switzerland, in dollars:

The currency in which data is given:

Transfer to US dollars and adjust for inflation:

### Moon Phases(1)

Create a lunar calendar in which the background color depends on the fraction of the moon illumination:

Create a new series of labeled images with gradient background:

Visualize the lunar calendar:

#### CMS

Wolfram Language. 2014. "TimeSeriesMapThread." Wolfram Language & System Documentation Center. Wolfram Research. https://reference.wolfram.com/language/ref/TimeSeriesMapThread.html.