Note that by multiplying the output of the randn function by σ and adding m, the Gaussian random variable produced by randn now has mean m and variance σ2. We will elaborate on such transformations and others in the next chapter. Note that the MATLAB code that follows is similar to ...
Estimate the mean and variance ofW=X2+Y2+Z2 by constructing a large number of realizations of this random variable in MATLAB and then computing the sample mean and sample variance. How many samples of the random variable were needed before the sample mean and sample variance seemed to ...
The ssm function returns an ssm object specifying the functional form and storing the parameter values of a standard linear Gaussian state-space model for a latent state process xt possibly imperfectly observed through the variable yt.
WhenAtis a coefficient matrix, For each state variablej, default values ofMean0andCov0depend onStateType(j): IfStateType(j) = 0(stationary state),bnlssmgenerates the initial value using the stationary distribution. If you provide all values in the coefficient matrices (that is, your model ha...
In addition, the function makes these assumptions: The variance of the complex-valued Gaussian random variable is divided equally among the real and imaginary parts. The real and imaginary parts are uncorrelated. Under these assumptions, the linear detection threshold for an NP detector is λσ=...
However, the sorting routine requires more computation resources, and can slow down computations, particularly in problems with a high-dimensional state variable. Example: SortParticles=true Data Types: logical RND— Previously generated normal random numbers structure array Previously generated normal ...
The observation equation is nonlinear. Becauseεtis a standard Gaussian random variable, the conditional distribution ofytgivenxtand the parameters is Gaussian with a mean of 0 and standard deviation√Δtexp(0.5xt). Thelocal functionparamMap, which uses the distribution form for the observation equa...
Open in MATLAB Online I have produced a Gaussian Randon Variable ranging between -3 to 3. I want to calculate the number of values greater than one standard deviation. How may I do that? ThemeCopy pd = makedist('Normal') x = -3:.1:3; pdf_normal...
The pre-defined Gaussian fitting function in the Curve Fitting App is defined slightly differently than the probability distribution function of a Gaussian random variable. Since the "Results" pane in the Curve Fitting App only displays the values of the model ...
ClassificationKernel is a trained model object for a binary Gaussian kernel classification model using random feature expansion. ClassificationKernel is more practical for big data applications that have large training sets but can also be applied to smaller data sets that fit in memory. Unlike other...