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X-13ARIMA-SEATS, successor to X-12-ARIMA and X-11, is a set of statistical methods for seasonal adjustment and other descriptive analysis of time series data that are implemented in the U.S. Census Bureau's software package. [3]
An example of statistical software for this type of decomposition is the program BV4.1 that is based on the Berlin procedure. The R statistical software also includes many packages for time series decomposition, such as seasonal, [7] stl, stlplus, [8] and bfast.
The seasonally adjusted annual rate (SAAR) is a rate that is adjusted to take into account typical seasonal fluctuations in data and is expressed as an annual total. SAARs are used for data affected by seasonality, when it could be misleading to directly compare different times of the year.
As the 2023 holiday season approaches, retail giant Target is gearing up to spread some extra cheer by hiring a whopping 100,000 seasonal employees across the United States. The majority of ...
Seasonal adjustment or deseasonalization is a statistical method for removing the seasonal component of a time series. It is usually done when wanting to analyse the trend, and cyclical deviations from trend, of a time series independently of the seasonal components.
In time series data, seasonality refers to the trends that occur at specific regular intervals less than a year, such as weekly, monthly, or quarterly. Seasonality may be caused by various factors, such as weather, vacation, and holidays [1] and consists of periodic, repetitive, and generally regular and predictable patterns in the levels [2] of a time series.
The purpose of the sales force compensation metric is to determine the mix of salary, bonus, and commission that will maximize sales generated by the sales force. When designing a compensation plan for a sales force, managers face four key considerations: level of pay, mix between salary and incentive, measures of performance, and performance-payout relationships.
Based on a selected periodicity, it is an alternative plot that emphasizes the seasonal patterns are where the data for each season are collected together in separate mini time plots. Seasonal subseries plots enables the underlying seasonal pattern to be seen clearly, and also shows the changes in seasonality over time. [2]