Traducción y análisis de palabras por inteligencia artificial ChatGPT
En esta página puede obtener un análisis detallado de una palabra o frase, producido utilizando la mejor tecnología de inteligencia artificial hasta la fecha:
- cómo se usa la palabra
- frecuencia de uso
- se utiliza con más frecuencia en el habla oral o escrita
- opciones de traducción
- ejemplos de uso (varias frases con traducción)
- etimología
average velocity model - traducción al ruso
сейсмология
модель средних скоростей
![Example of a velocity vs. time graph, and the relationship between velocity '''''v''''' on the y-axis, acceleration '''''a''''' (the three green [[tangent]] lines represent the values for acceleration at different points along the curve) and displacement '''''s''''' (the yellow [[area]] under the curve.)](https://commons.wikimedia.org/wiki/Special:FilePath/Velocity vs time graph.svg?width=200 "Example of a velocity vs. time graph, and the relationship between velocity '''''v''''' on the y-axis, acceleration '''''a''''' (the three green [[tangent]] lines represent the values for acceleration at different points along the curve) and displacement '''''s''''' (the yellow [[area]] under the curve.)")
общая лексика
вектор скорости
- velocity of circulation
- velocity of currency
- velocity of money
- velocity of turnover
- adjustment velocity
- business transactions velocity
- circuit velocity of money
- consumption velocity
- income velocity
- income velocity of money
- output velocity
- price velocity
- sectoral velocity
- transaction velocity
- transaction velocity of money
Definición
Wikipedia
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 , 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.
