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  2. Unit root - Wikipedia

    en.wikipedia.org/wiki/Unit_root

    In probability theory and statistics, a unit root is a feature of some stochastic processes (such as random walks) that can cause problems in statistical inference involving time series models. A linear stochastic process has a unit root if 1 is a root of the process's characteristic equation .

  3. Unit root test - Wikipedia

    en.wikipedia.org/wiki/Unit_root_test

    In statistics, a unit root test tests whether a time series variable is non-stationary and possesses a unit root. The null hypothesis is generally defined as the presence of a unit root and the alternative hypothesis is either stationarity , trend stationarity or explosive root depending on the test used.

  4. Random walk - Wikipedia

    en.wikipedia.org/wiki/Random_walk

    Five eight-step random walks from a central point. Some paths appear shorter than eight steps where the route has doubled back on itself. (animated version)In mathematics, a random walk, sometimes known as a drunkard's walk, is a stochastic process that describes a path that consists of a succession of random steps on some mathematical space.

  5. Probability theory - Wikipedia

    en.wikipedia.org/wiki/Probability_theory

    Probability theory or probability calculus is the branch of mathematics concerned with probability. Although there are several different probability interpretations , probability theory treats the concept in a rigorous mathematical manner by expressing it through a set of axioms .

  6. Information gain (decision tree) - Wikipedia

    en.wikipedia.org/wiki/Information_gain_(decision...

    Note: () will be the same for all mutations at the root. The relatively high value of entropy H ( t ) = 0.985 {\displaystyle \mathrm {H} {(t)}=0.985} (1 is the optimal value) suggests that the root node is highly impure and the constituents of the input at the root node would look like the leftmost figure in the above Entropy Diagram .

  7. Autoregressive model - Wikipedia

    en.wikipedia.org/wiki/Autoregressive_model

    In statistics, econometrics, and signal processing, an autoregressive (AR) model is a representation of a type of random process; as such, it can be used to describe certain time-varying processes in nature, economics, behavior, etc.

  8. Dickey–Fuller test - Wikipedia

    en.wikipedia.org/wiki/Dickey–Fuller_test

    Which of the three main versions of the test should be used is not a minor issue. The decision is important for the size of the unit root test (the probability of rejecting the null hypothesis of a unit root when there is one) and the power of the unit root test (the probability of rejecting the null hypothesis of a unit root when there is not one).

  9. Stationary process - Wikipedia

    en.wikipedia.org/wiki/Stationary_process

    A trend-stationary process is not strictly stationary but can be made stationary by removing the trend. Similarly, processes with unit roots can be made stationary through differencing. Another type of non-stationary process, distinct from those with trends, is a cyclostationary process, which exhibits cyclical variations over time.