SER Y=MA(X,<weight_description>) TO <data> computes moving averages of X to Y according to <weight_description>. <weight_description> can be any of the three alternatives: 1) List of weights SER Temp2=MA(Temp,1,2,3,0,0) i.e. Temp2[t]=1*Temp[t-2]+2*Temp[t-1]+3*Temp[t]+0*Temp[t+1]+0*Temp[t+1] or SER Temp3=MA(Temp,1,2,3,*) being equivalent to SER Temp3=MA(Temp,1,2,3,2,1) (symmetric weights) Number of weights must be uneven. 2) Name of a weight pattern SER TempS=MA(Temp,SPENCER) The weights for SPENCER must be given in the same edit field as SPENCER=-3,-6,-5,3,21,46,67,74,* 3) Weights for polynomial trends SER Temp4=MA(Temp,P3:21) fits a cubic (P3) to sets of 21 points. Generally Pp:m implies fitting of a polynomial of degree p with a span of m consecutive points. m must be an odd integer. In all cases above, the sum of weights is scaled to 1. SER Y=MAE(X,<weight_description>) TO <data> works as MA, but provides trend values for the first and last m values of the series as well. MAE works only in the case of polynomial weights. SER Y=MA(X,<weight_description>) TO <data> / PERIOD=s works similarly, but uses values ..., X[t-3s], X[t-2s], X[t-s], X[t], X[t+s], X[t+2s], X[t+3s], ... instead of ..., X[t-3], X[t-2], X[t-1], X[t], X[t+1], X[t+2], X[t+3], ... The period s is given as an extra specification PERIOD=s. Another way to enter the period s (say for s=3) is to use the operation SER Y=MA3(X,<weight_description>) TO <data> . SER Y=MAE(X,<weight_description>) TO <data> / PERIOD=s provides smoothened values for the first and last observations as well (in case of polynomial weights). Alternative notation is Y=MAE3(X,... for s=3. S = More information on SER operations

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