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  2. Kernel regression - Wikipedia

    en.wikipedia.org/wiki/Kernel_regression

    In statistics, kernel regression is a non-parametric technique to estimate the conditional expectation of a random variable.The objective is to find a non-linear relation between a pair of random variables X and Y.

  3. Kernel (statistics) - Wikipedia

    en.wikipedia.org/wiki/Kernel_(statistics)

    The first requirement ensures that the method of kernel density estimation results in a probability density function. The second requirement ensures that the average of the corresponding distribution is equal to that of the sample used. If K is a kernel, then so is the function K* defined by K*(u) = λK(λu), where λ > 0. This can be used to ...

  4. Kernel smoother - Wikipedia

    en.wikipedia.org/wiki/Kernel_smoother

    Kernel average smoother example. The idea of the kernel average smoother is the following. For each data point X 0, choose a constant distance size λ (kernel radius, or window width for p = 1 dimension), and compute a weighted average for all data points that are closer than to X 0 (the closer to X 0 points get higher weights).

  5. Law of total variance - Wikipedia

    en.wikipedia.org/wiki/Law_of_total_variance

    Then the first, "unexplained" term on the right-hand side of the above formula is the weighted average of the variances, hσ h 2 + (1 − h)σ t 2, and the second, "explained" term is the variance of the distribution that gives μ h with probability h and gives μ t with probability 1 − h.

  6. Quantile regression - Wikipedia

    en.wikipedia.org/wiki/Quantile_regression

    Quantile regression is a type of regression analysis used in statistics and econometrics. Whereas the method of least squares estimates the conditional mean of the response variable across values of the predictor variables, quantile regression estimates the conditional median (or other quantiles) of the response variable.

  7. Autoregressive conditional heteroskedasticity - Wikipedia

    en.wikipedia.org/wiki/Autoregressive_conditional...

    Exponentially weighted moving average (EWMA) is an alternative model in a separate class of exponential smoothing models. As an alternative to GARCH modelling it has some attractive properties such as a greater weight upon more recent observations, but also drawbacks such as an arbitrary decay factor that introduces subjectivity into the ...

  8. Tail value at risk - Wikipedia

    en.wikipedia.org/wiki/Tail_value_at_risk

    A common case in literature is to define TVaR and average value at risk as the same measure. [1] Under some formulations, it is only equivalent to expected shortfall when the underlying distribution function is continuous at VaR α ⁡ ( X ) {\displaystyle \operatorname {VaR} _{\alpha }(X)} , the value at risk of level α {\displaystyle \alpha ...

  9. Conditional expectation - Wikipedia

    en.wikipedia.org/wiki/Conditional_expectation

    The unconditional expectation of rainfall for an unspecified day is the average of the rainfall amounts for those 3652 days. The conditional expectation of rainfall for an otherwise unspecified day known to be (conditional on being) in the month of March, is the average of daily rainfall over all 310 days of the ten–year period that fall in ...