autoregressive operator - перевод на русский
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autoregressive operator - перевод на русский

STATISTICAL MODEL USED IN TIME SERIES ANALYSIS
Autoregressive moving average; ARMAX; Autoregressive moving average model; ARMA model; Autoregressive moving-average model; Autoregressive-moving-average model

autoregressive operator      

математика

оператор авторегрессии

nabla operator         
  • DCG chart:

A simple chart depicting all rules pertaining to second derivatives.
D, C, G, L and CC stand for divergence, curl, gradient, Laplacian and curl of curl, respectively.

Arrows indicate existence of second derivatives. Blue circle in the middle represents curl of curl, whereas the other two red circles (dashed) mean that DD and GG do not exist.
  • Del operator,<br />represented by<br />the [[nabla symbol]]
VECTOR'S DIFFERENTIAL OPERATOR
Nabla constant; Atled; Nabla operator; Del operator; Vector differential; Vector differential operator; Gradient operator; Divergence operator

общая лексика

оператор набла

vector differential         
  • DCG chart:

A simple chart depicting all rules pertaining to second derivatives.
D, C, G, L and CC stand for divergence, curl, gradient, Laplacian and curl of curl, respectively.

Arrows indicate existence of second derivatives. Blue circle in the middle represents curl of curl, whereas the other two red circles (dashed) mean that DD and GG do not exist.
  • Del operator,<br />represented by<br />the [[nabla symbol]]
VECTOR'S DIFFERENTIAL OPERATOR
Nabla constant; Atled; Nabla operator; Del operator; Vector differential; Vector differential operator; Gradient operator; Divergence operator

математика

векторный дифференциал

Определение

Del

Википедия

Autoregressive–moving-average model

In the statistical analysis of time series, autoregressive–moving-average (ARMA) models provide a parsimonious description of a (weakly) stationary stochastic process in terms of two polynomials, one for the autoregression (AR) and the second for the moving average (MA). The general ARMA model was described in the 1951 thesis of Peter Whittle, Hypothesis testing in time series analysis, and it was popularized in the 1970 book by George E. P. Box and Gwilym Jenkins.

Given a time series of data X t {\displaystyle X_{t}} , the ARMA model is a tool for understanding and, perhaps, predicting future values in this series. The AR part involves regressing the variable on its own lagged (i.e., past) values. The MA part involves modeling the error term as a linear combination of error terms occurring contemporaneously and at various times in the past. The model is usually referred to as the ARMA(p,q) model where p is the order of the AR part and q is the order of the MA part (as defined below).

ARMA models can be estimated by using the Box–Jenkins method.

Как переводится autoregressive operator на Русский язык