Calendar Effects in Monthly Time Series: Detection by Spectrum Analysis and Graphical Methods Export

@article{citeulike:6097055, abstract = {Many time series, particularly national business and economic series, which are reported monthly and represent a total of the series for each month, contain calendar effects due to changing month length, weekly periodicities, and holidays. It is important to detect and remove this spurious calendar variation to allow a better appreciation of the variation in the series due to important factors. This article discusses detection. Two sets of diagnostic methods for detecting calendar effects in monthly time series, spectrum analyses and time domain graphical displays, are described. These methods can be used in an initial analysis to decide if calendar adjustment is necessary and can be used on an adjusted series to determine if the adjustment has properly removed all of the calendar effects.}, author = {Cleveland, William S. and Devlin, Susan J.}, citeulike-article-id = {6097055}, citeulike-linkout-0 = {http://dx.doi.org/10.2307/2287636}, citeulike-linkout-1 = {http://www.jstor.org/stable/2287636}, doi = {10.2307/2287636}, issn = {01621459}, journal = {Journal of the American Statistical Association}, keywords = {graphical\_methods, seasonal\_adjustment}, number = {371}, pages = {487--496}, posted-at = {2009-11-11 07:43:23}, priority = {2}, publisher = {American Statistical Association}, title = {Calendar Effects in Monthly Time Series: Detection by Spectrum Analysis and Graphical Methods}, url = {http://dx.doi.org/10.2307/2287636}, volume = {75}, year = {1980} }

TY - JOUR ID - citeulike:6097055 L3 - citeulike-article-id:6097055 N2 - Many time series, particularly national business and economic series, which are reported monthly and represent a total of the series for each month, contain calendar effects due to changing month length, weekly periodicities, and holidays. It is important to detect and remove this spurious calendar variation to allow a better appreciation of the variation in the series due to important factors. This article discusses detection. Two sets of diagnostic methods for detecting calendar effects in monthly time series, spectrum analyses and time domain graphical displays, are described. These methods can be used in an initial analysis to decide if calendar adjustment is necessary and can be used on an adjusted series to determine if the adjustment has properly removed all of the calendar effects. IS - 371 JF - Journal of the American Statistical Association SN - 01621459 EP - 496 TI - Calendar Effects in Monthly Time Series: Detection by Spectrum Analysis and Graphical Methods PB - American Statistical Association VL - 75 SP - 487 KW - graphical_methods KW - seasonal_adjustment AU - Cleveland, William AU - Devlin, Susan PY - 1980/// UR - http://dx.doi.org/10.2307/2287636 ER -