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  2. Autoregressive moving-average model - Wikipedia

    en.wikipedia.org/wiki/Autoregressive_moving...

    MATLAB includes functions such as arma, ar and arx to estimate autoregressive, exogenous autoregressive and ARMAX models. See System Identification Toolbox and Econometrics Toolbox for details. Julia has community-driven packages that implement fitting with an ARMA model such as arma.jl.

  3. Box–Jenkins method - Wikipedia

    en.wikipedia.org/wiki/Box–Jenkins_method

    The sample autocorrelation plot and the sample partial autocorrelation plot are compared to the theoretical behavior of these plots when the order is known. Specifically, for an AR(1) process, the sample autocorrelation function should have an exponentially decreasing appearance. However, higher-order AR processes are often a mixture of ...

  4. Autoregressive model - Wikipedia

    en.wikipedia.org/wiki/Autoregressive_model

    Together with the moving-average (MA) model, it is a special case and key component of the more general autoregressive–moving-average (ARMA) and autoregressive integrated moving average (ARIMA) models of time series, which have a more complicated stochastic structure; it is also a special case of the vector autoregressive model (VAR), which ...

  5. How to calculate loan payments and costs - AOL

    www.aol.com/finance/calculate-loan-payments...

    Using a loan calculator can help determine the exact monthly payments for a loan, making it easier to budget and avoid mistakes. ... Examples of amortizing loans include car loans, mortgages and ...

  6. Here's how to calculate the cost of your next car loan. - AOL

    www.aol.com/heres-calculate-cost-next-car...

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  7. How to calculate interest on a car loan - AOL

    www.aol.com/finance/calculate-interest-car-loan...

    As with other types of loans, the overall cost of a car loan comes down to one major factor: the annual percentage rate. The APR includes both interest and lender fees, expressed as a percentage.

  8. Autoregressive integrated moving average - Wikipedia

    en.wikipedia.org/wiki/Autoregressive_integrated...

    Non-seasonal ARIMA models are usually denoted ARIMA(p, d, q) where parameters p, d, q are non-negative integers: p is the order (number of time lags) of the autoregressive model, d is the degree of differencing (the number of times the data have had past values subtracted), and q is the order of the moving-average model.

  9. The enhancement to ordinary ARMA models is as follows: Take the original data series and high-pass filter it with fractional differencing enough to make the result stationary, and remember the order d of this fractional difference, d usually between 0 and 1 ... possibly up to 2+ in more extreme cases.