income smoothing - translation to ρωσικά
Display virtual keyboard interface

income smoothing - translation to ρωσικά

GENERATES A FORECAST OF FUTURE VALUES OF A TIME SERIES
Expenential Smoothing; Holt-Winters; Double exponential smoothing; Peter R. Winters

income smoothing      

управление

выравнивание доходов (сглаживание колебаний доходов за рассматриваемый период; может быть следствием искажений в учете некоторых статей (напр., путем переноса будущих доходов на текущий период или несвоевременного списания на убытки сомнительных долгов); в итоге экономические результаты выглядят не такими, какие они есть, а такими, какими руководству выгодно их представить инвесторам, партнерам и т. д.)

Смотрите также

window dressing

data smoothing         
DATASET MODIFICATION USING AN APPROXIMATING FUNCTION TO CAPTURE IMPORTANT PATTERNS IN THE DATA WHILE LEAVING OUT NOISE
Smoothed; Smoothes; Smoothly; Smoothest; Smoothdown; Smooth-down; Smoothes down; Smoothed down; Smoothing down; Data smoothing; Adaptive smoothening; Adaptive smoothing; Algorithms for smoothing; Smoothing algorithms

общая лексика

осреднение данных

mean income         
MACROECONOMIC INDICATOR
Per-capita income; Personal per capita income; Pro capite income; Median family income; PerCapitaIncome; Income per capita; Medium income; Low income households; List of countries by median wage; List of countries by median income; Per capita personal income; Median household income; Mean income; Countries by median income; Median total household income; List of median wages by country
средний доход

Ορισμός

income tax
¦ noun tax levied directly on personal income.

Βικιπαίδεια

Exponential smoothing

Exponential smoothing is a rule of thumb technique for smoothing time series data using the exponential window function. Whereas in the simple moving average the past observations are weighted equally, exponential functions are used to assign exponentially decreasing weights over time. It is an easily learned and easily applied procedure for making some determination based on prior assumptions by the user, such as seasonality. Exponential smoothing is often used for analysis of time-series data.

Exponential smoothing is one of many window functions commonly applied to smooth data in signal processing, acting as low-pass filters to remove high-frequency noise. This method is preceded by Poisson's use of recursive exponential window functions in convolutions from the 19th century, as well as Kolmogorov and Zurbenko's use of recursive moving averages from their studies of turbulence in the 1940s.

The raw data sequence is often represented by { x t } {\displaystyle \{x_{t}\}} beginning at time t = 0 {\displaystyle t=0} , and the output of the exponential smoothing algorithm is commonly written as { s t } {\displaystyle \{s_{t}\}} , which may be regarded as a best estimate of what the next value of x {\displaystyle x} will be. When the sequence of observations begins at time t = 0 {\displaystyle t=0} , the simplest form of exponential smoothing is given by the formulas:

s 0 = x 0 s t = α x t + ( 1 α ) s t 1 , t > 0 {\displaystyle {\begin{aligned}s_{0}&=x_{0}\\s_{t}&=\alpha x_{t}+(1-\alpha )s_{t-1},\quad t>0\end{aligned}}}

where α {\displaystyle \alpha } is the smoothing factor, and 0 < α < 1 {\displaystyle 0<\alpha <1} .

Μετάφραση του &#39income smoothing&#39 σε Ρωσικά