Detrend

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Detrend

To remove the general drift, tendency, or bent of a set of statistical data as related to time. Often accomplished by regressing a variable or a time index and perhaps the square of the time index and capturing the residuals. A stochastic detrend would be to subtract a moving-average (say for five years) from the value of the variable.

Detrend

The removal of a trend from the consideration of several variables. A detrend may be necessary to discover a company's true financial health. For example, one may detrend increased sales around Christmas time to see a more accurate account of a company's sales in a given year.
References in periodicals archive ?
Detrending the series of sales and earnings leads to generally lower DOL estimates, except for the Value portfolio.
To this end, Table 4 reports results from unit root tests for the series used in the VARs that follow, both before and after detrending.
The detrending assumes that the log real variables are driven by a broken linear trend, with constant and trend breaks in both 1973:Q4 and 1981:Q4.
See Canova (1998) for a discussion of various detrending filters and their impact on the perceived business cycle facts.
This gives the NKPC its forward-looking character, which is developed by linearizing the price aggregator (1) and the optimal price rule (3), subsequent to detrending, to construct
Also, the slope of the line relating the elevation profile detrending (1) length to some power of the detrended root mean squared (RMS) (2) value is used.
The detrending methods may also differ in terms of whether or not the resulting cyclical series is stationary, i.
9] Further, the results are robust to the choice of time period and detrending methodology, and the DW statistics show no evidence of serial correlation.
But for the early '60s and the late '90s the message would be quite different, with lower interest rates indicated by the gap based on the log-linear detrending.
Prediction equations were developed using modified partial least squares regression with two outlier elimination passes and six cross-validation groups, with and without spectral data transformation via standard normal variate with detrending (SNV-D).
We used the following options: detrending by segments, nonlinear rescaling, and down-weighting of rare species to reduce the often detrimental influence of ecologically uninformative species on the ordination axes.
Briefly, the technique initially involved two successive detrending procedures to reduce the overall growth trend in each series by producing time series that were stationary in mean and variance: a linear or negative exponential trend line was followed by a spline curve.
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