Assessing Seasonality Variation with Harmonic Regression: Accommodations for Sharp Peaks

International Journal of Environmental Research and Public Health

Mani Thenmozhi¹  Lakshmanan Jeyaseelan¹  Kavitha Ramanathan¹  Shalini Anandan²  Balaji Veeraraghavan²  Sebastian George³  ElenaN. Naumova⁴ 

[1] Department of Biostatistics, Christian Medical College, Vellore 632002, India;Department of Clinical Microbiology, Christian Medical College, Vellore 632004, India;Department of Statistics, St. Thomas College, Palai, Kerala 686575, India;Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA 02111, USA;

关键词: time series;    harmonic regression;    seasonality;    infectious disease;    arima/sarima;    trends;   

DOI  :  10.3390/ijerph17041318

来源: DOAJ

【 摘 要 】

The use of the harmonic regression model is well accepted in the epidemiological and biostatistical communities as a standard procedure to examine seasonal patterns in disease occurrence. While these models may provide good fit to periodic patterns with relatively symmetric rises and falls, for some diseases the incidence fluctuates in a more complex manner. We propose a two-step harmonic regression approach to improve the model fit for data exhibiting sharp seasonal peaks. To capture such specific behavior, we first build a basic model and estimate the seasonal peak. At the second step, we apply an extended model using sine and cosine transform functions. These newly proposed functions mimic a quadratic term in the harmonic regression models and thus allow us to better fit the seasonal spikes. We illustrate the proposed method using actual and simulated data and recommend the new approach to assess seasonality in a broad spectrum of diseases manifesting sharp seasonal peaks.

【 授权许可】

Unknown