Seasonal effects are dominant in many environmental time series and important or at least notable in many economic or biomedical time series, to name only a few application areas represented in the Stata user community. In several fields it seems rare to use anything other than basic line graphs of responses versus time to display series showing seasonality. The presentation focuses on a variety of minor and major tricks for examining seasonality graphically, some of which have long histories in climatology or related sciences, but appear little known outside. Some original code will be discussed, but the greater emphasis is on users needing to know Stata functions and commands well if they are to exploit the full potential of its graphics.
Graphs are important for highlighting relationships within a data series or across several series. M...
This chapter reviews the principal methods used by researchers when forecasting seasonal time series...
Classical time series analysis has well known methods for the study of seasonality. A more recent me...
Time series showing seasonality—marked variation with time of year—are of interest to many scientist...
Many economic time series exhibit important systematic fluctuations within the year, i.e., seasonali...
Many common diseases, such as the flu and cardiovascular disease, increase markedly in winter and di...
The traditional literature on seasonality has mainly focused attention on various statistical proced...
Many of the Census Bureau's economic surveys publish seasonally adjusted data. As producers of ...
A procedure is introduced for the analysis of seasonal trends in time series of Earth observation im...
Abstract Many common diseases, such as the flu and cardiovascular disease, increase markedly in wint...
Seasonal adjustment o f monthly and q uarterly d ata is q uite p revalent in many statistical agenci...
Methodology for seasonality diagnostics is extremely important for statistical agencies, because suc...
Background. Epldemlological inferences about the aetiology of a disease can often be made from Its s...
We present a method for investigating the evolution of trend and seasonality in an observed time ser...
Seasonal patterns have been found in a remarkable range of health conditions, including birth defect...
Graphs are important for highlighting relationships within a data series or across several series. M...
This chapter reviews the principal methods used by researchers when forecasting seasonal time series...
Classical time series analysis has well known methods for the study of seasonality. A more recent me...
Time series showing seasonality—marked variation with time of year—are of interest to many scientist...
Many economic time series exhibit important systematic fluctuations within the year, i.e., seasonali...
Many common diseases, such as the flu and cardiovascular disease, increase markedly in winter and di...
The traditional literature on seasonality has mainly focused attention on various statistical proced...
Many of the Census Bureau's economic surveys publish seasonally adjusted data. As producers of ...
A procedure is introduced for the analysis of seasonal trends in time series of Earth observation im...
Abstract Many common diseases, such as the flu and cardiovascular disease, increase markedly in wint...
Seasonal adjustment o f monthly and q uarterly d ata is q uite p revalent in many statistical agenci...
Methodology for seasonality diagnostics is extremely important for statistical agencies, because suc...
Background. Epldemlological inferences about the aetiology of a disease can often be made from Its s...
We present a method for investigating the evolution of trend and seasonality in an observed time ser...
Seasonal patterns have been found in a remarkable range of health conditions, including birth defect...
Graphs are important for highlighting relationships within a data series or across several series. M...
This chapter reviews the principal methods used by researchers when forecasting seasonal time series...
Classical time series analysis has well known methods for the study of seasonality. A more recent me...