A NOTE ON LIKELIHOOD ESTIMATION OF MISSING VALUES IN TIME-SERIES

被引:10
作者
PENA, D [1 ]
TIAO, GC [1 ]
机构
[1] UNIV CHICAGO,GRAD SCH BUSINESS,CHICAGO,IL 60637
关键词
ARIMA MODELS; INTERPOLATION; MEAN SQUARED ERROR;
D O I
10.2307/2684292
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
Missing values in time series can be treated as unknown parameters and estimated by maximum likelihood or as random variables and predicted by the expectation of the unknown values given the data. The difference between these two procedures is illustrated by an example. It is argued that the second procedure is, in general, more relevant for estimating missing values in times series.
引用
收藏
页码:212 / 213
页数:2
相关论文
共 5 条
[1]  
BAYARRI MJ, 1986, 4TH P PURD S STAT DE, P3
[2]  
Box G.E.P., 1992, BAYESIAN INFERENCE S
[3]  
Brubacher S. R., 1976, Applied Statistics, V25, P107, DOI 10.2307/2346678
[4]  
Fuller WA, 1987, MEASUREMENT ERRORS M
[5]  
Pena D., 1987, NEW PERSPECTIVES THE, P109