In econometrics, the autoregressive conditional heteroskedasticity (ARCH) model is a statistical model for time series data that describes the variance... 23 KB (3,503 words) - 04:43, 19 March 2024 |
In statistics, econometrics, and signal processing, an autoregressive (AR) model is a representation of a type of random process; as such, it is used to... 34 KB (4,897 words) - 18:06, 13 March 2024 |
variances are important parts of autoregressive conditional heteroskedasticity (ARCH) models. The conditional variance of a random variable Y given another... 6 KB (1,085 words) - 03:19, 13 March 2024 |
generalized in other ways. See also autoregressive conditional heteroskedasticity (ARCH) models and autoregressive integrated moving average (ARIMA) models... 20 KB (2,613 words) - 15:54, 27 March 2024 |
Homoscedasticity and heteroscedasticity (redirect from Heteroskedasticity) White, Halbert (1980). "A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity". Econometrica. 48 (4): 817–838... 27 KB (3,101 words) - 19:52, 25 February 2024 |
Vector autoregression (redirect from Vector autoregressive model) process model. VAR models generalize the single-variable (univariate) autoregressive model by allowing for multivariate time series. VAR models are often... 22 KB (3,235 words) - 13:19, 3 July 2023 |
is no linear relationship. The partial correlation coincides with the conditional correlation if the random variables are jointly distributed as the multivariate... 22 KB (3,140 words) - 17:13, 24 September 2023 |
moving average (EWMA). Technically it can also be classified as an autoregressive integrated moving average (ARIMA) (0,1,1) model with no constant term... 25 KB (3,845 words) - 15:00, 10 January 2024 |