A First Course on Time Series Analysis : Examples with SAS - download pdf or read online

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By Michael Falk

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7. 2 lists total numbers of unemployed (in thousands) in West Germany between 1950 and 1993. Compare a logistic trend function with an allometric one. Which one gives the better fit? 8. Give an update equation for a simple moving average of (even) order 2s. 9. 3 lists West Germany’s public expenditures (in billion D-Marks) between 1961 and 1990. Compute simple moving averages of order 3 and 5 to estimate a possible trend. Plot the original data as well as the filtered ones and compare the curves.

17). 19. Show that lim Tλ (Yt ) = T0 (Yt ) = log(Yt ), λ↓0 for the Box–Cox transformation Tλ . Yt > 0 Chapter Models of Time Series Each time series Y1 , . . , Yn can be viewed as a clipping from a sequence of random variables . . , Y−2 , Y−1 , Y0 , Y1 , Y2 , . . In the following we will introduce several models for such a stochastic process Yt with index set Z. 1 Linear Filters and Stochastic Processes For mathematical convenience we will consider complex valued random variables Y , whose range is √ the set of complex numbers C = {u + iv : u, v ∈ R}, where i = −1.

1 2 3 /* e l e c t r i c i t y _ d i f f e r e n c e s . sas */ TITLE1 ’ First and second order differences ’; TITLE2 ’ Electricity Data ’; 4 5 6 7 8 9 10 11 12 /* Read in the data , compute moving average of length as 12 as well as first and second order differences */ DATA data1 ( KEEP = year sum delta1 delta2 ) ; INFILE ’c :\ data \ electric . 2 Linear Filtering of Time Series 31 17 18 19 20 21 22 23 24 /* Generate three plots */ GOPTIONS NODISPLAY ; PROC GPLOT DATA = data1 GOUT = fig ; PLOT sum * year / VAXIS = AXIS1 HAXIS = AXIS2 ; PLOT delta1 * year / VAXIS = AXIS1 VREF =0; PLOT delta2 * year / VAXIS = AXIS1 VREF =0; RUN ; 25 26 27 28 29 30 31 /* Display them in one output */ GOPTIONS DISPLAY ; PROC GREPLAY NOFS IGOUT = fig TC = SASHELP .

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A First Course on Time Series Analysis : Examples with SAS by Michael Falk


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