Sentences with phrase «distribution of a random variable»

It represents the distribution of a random variable in the form of a bell curve, with the exact shape defined by the expected value and the standard deviation.

On the other hand, the distribution of the random variable L = g (X), depends on the specific shape of the density function and so will generally differ from distribution to distribution.

The computation of entropy requires information on the probability distribution of the random variable p (xl).

Not exact matches

The fixed effects of the proportion of rainbow trout admixture, sex, fish length (covariates) and spawning year (random effect) on reproductive success (response variable) were evaluated using generalized linear mixed models (GLMMs) using a natural log - link function with a quasi-Poisson error distribution (see the electronic supplementary material).

At any such point, is a random variable with Still conditioning on, consider counterfactual outcomes as varies over, averaging over the conditional distribution of given: There is a structural function interpretation for: within a school with, we can obtain potential expected output for various assigned values of the teacher input, holding constant the distribution of classroom characteristics (at the conditional distribution of given).

The central limit theorem says that the distribution of the mean of a bunch of independent random variables tends to be gaussian with variance that is the sum of the individual variances.

(1) IF you consider the distribution of a sum of independent gaussian random variables the variance is the sum of the variances of the individual variables.

In particular, the model is based on an ECS distribution defined as a random variable modeling «the equilibrium global average surface warming following a doubling of CO2 concentration.»

«Thus far the data have been assumed to consist of the trend plus noise, with the noise at each data point being independent and identically distributed random variables and to have a normal distribution.

which would remove all the problems with ratio distributions and make it a problem of a product of random variables.

Gregory 02 in fact computed the probability distribution of the climate sensitivity directly from the random samples of the variables.

that, taking advantage of the fact that the Beta distribution is a conjugate prior for the binomial likelihood, and that Beta (1,1) ≡ Unif (0,1), and finally that the Beta distribution is so flexible for any continuous random variable defined on the unit interval [including the Jeffreys prior ≡ Beta (1/2, 1/2)-RSB-, that you can express the mean of the posterior distribution, which itself is another Beta, as a weighted average.

If we want to obtain a function T (x, y, z, t) obeying certain non linear PED / ODE we will look for a PARTICULAR type type of solution: T (x, y, z, t) = Ta (x, y, z) + u (x, y, z, t) where Ta (x, y, z) is a time average of T (x, y, z, t) over a certain period L (eventually a bit space averaged around the point (x, y, z)-RRB- AND u (x, y, z, t) is a random variable with a known probability density distribution.

Generaly we only dream about that:) It describes everything one needs for any imaginable analysis and there is plenty of things to tell about a random variable whose distribution one knows.

Non-climatic environmental factors will certainly have been important for individual trees at different times, but these factors are regarded as haphazard events with random distribution over space and time and, hence, they can be regarded as part of the random error variable (ε t) in the conceptual linear aggregate equation (Eq.