Routines for the seasonal analysis of health data, including regression models, time-stratified case-crossover, plotting functions and residual checks, see Barnett and Dobson (2010) ISBN 978-3-642-10748-1. Thanks to Yuming Guo for checking the case-crossover code.

Easy-to-use interface to X-13-ARIMA-SEATS, the seasonal adjustment
    software by the US Census Bureau. It offers full access to almost all
    options and outputs of X-13, including X-11 and SEATS, automatic ARIMA model
    search, outlier detection and support for user defined holiday variables,
    such as Chinese New Year or Indian Diwali. A graphical user interface can be
    used through the 'seasonalview' package. Uses the X-13-binaries from the
    'x13binary' package.

The price action at any given time is determined by investor 
  sentiment and market conditions. Although there is no established principle, 
  over a long period of time, things often move with a certain periodicity.
  This is sometimes referred to as anomaly. 
  The seasonPlot() function in this package calculates and visualizes the 
  average value of price movements over a year for any given period. 
  In addition, the monthly increase or decrease in price movement is 
  represented with a colored background. 
  This seasonPlot() function can use the same symbols as the 'quantmod' package 
  (e.g. ^IXIC, ^DJI, SPY, BTC-USD, and ETH-USD etc).

A graphical user interface to the 'seasonal' package and
  'X-13ARIMA-SEATS', the U.S. Census Bureau's seasonal adjustment software. 
  Unifies the code base of <http://www.seasonal.website> and the GUI in the
  'seasonal' package.

An overall test for seasonality of a given time
    series in addition to a set of individual seasonality tests as
    described by Ollech and Webel (forthcoming): An overall seasonality
    test. Bundesbank Discussion Paper.

Provides tools for processing and evaluating seasonal weather forecasts, 
    with an emphasis on tercile forecasts. We follow the World Meteorological Organization's 
    "Guidance on Verification of Operational Seasonal Climate Forecasts", 
    S.J.Mason (2018, ISBN: 978-92-63-11220-0, URL: <https://library.wmo.int/idurl/4/56227>). 
    The development was supported by the European Union’s Horizon 2020 research and innovation 
    programme under grant agreement no. 869730 (CONFER).
    A comprehensive online tutorial is available at <http://files.nr.no/samba/CONFER/SeaVal/>.