Time Series Interpolation and Frequency Conversion
The EXPAND procedure provides time interval conversion
and missing value interpolation for time series.
The EXPAND procedure includes the following features:
- conversion of time series frequency;
for example, constructing quarterly estimates from annual series
or aggregating quarterly values to annual values
- conversion of irregular observations to periodic observations
- interpolation of missing values in time series
- conversion of observation types; for example, estimate
stocks from flows and vice versa.
All possible conversions supported between
- beginning of period
- end of period
- period midpoint
- period total
- period average
- conversion of time series phase shift; for example,
conversion between fiscal years and calendar years
- choice of four interpolation methods:
- cubic splines
- linear splines
- step functions
- simple aggregation
- ability to transform series before and after interpolation
(or without interpolation) using:
- constant shift or scale
- sign change or absolute value
- logarithm, exponential, square root, square, logistic, inverse logistic
- lags, leads, differences
- classical decomposition
- bounds, trims, reverse series
- centered moving, cumulative, or backward moving average
- centered moving, cumulative, or backward moving corrected sum of squares
- centered moving, cumulative, or backward moving sum
- centered moving, cumulative, or backward moving median
- centered moving, cumulative, or backward moving variance
- support for a wide range of time series frequencies:
- YEAR
- SEMIYEAR
- QUARTER
- MONTH
- SEMIMONTH
- TENDAY
- WEEK
- WEEKDAY
- DAY
- HOUR
- MINUTE
- SECOND
- The basic interval types can be repeated or shifted to define a
great variety of different frequencies,
such as fiscal years, biennial periods, work shifts, and so forth.
Copyright © 1999 by SAS Institute Inc., Cary, NC, USA. All rights reserved.
