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In Wikipedia, the method of moments uses only ordinary moments: One starts with deriving equations that related the population moments (i.e., the expected values of powers of the random variable … under consideration) to the parameters of interest What if the method of moments uses other types of moments, such as central moments or standardized moments? …

I have been reading about the method of moments, and now I understand how to obtain the method of moments estimator for a random sample $x_1,...,x_n$ from a distribution $f(x;\theta)$, in the multiparameter … However, I fail to see how to formulate the method of moments for the linear regression model $$y_i = x_i^T\beta + e_i,$$ where $E[e_i]=0$, $\beta,xi\in R^p$. …

I was looking for a book that could explain me well the Generalized Method of Moments, its mathematical nuances, and even have a look to the empirical side, maybe with some guided exercises with Stata …

The parameters of a t distribution can be estimated via maximum-likelihood estimation (ML) or method of moments (MM) If we use the method of moments we have: $$\mu=E(R)$$ $$\sigma^2=V(R)=\frac{\beta …

Use the method of moments to obtain an estimate for the total population. … The method of moments is a way to estimate the parameters by gathering a system of equations using empirical moments and setting them equal to the actual moments. …

In Method of Moments for estimation, if there are $k$ parameters to estimate, we usually consider $i$-th moments, $i=1,...,k$, so that we have k equations for k unknowns. … Also would it be better if we choose moments of other orders, instead of $i=1,...,k$? …

Let $x_1=2, x_2 = 1, x_3 = \sqrt5, x_4 = \sqrt2$ be the observed values of a random sample of size 4 from a uniform distribution $U(-\theta, \theta)$ where $\theta>0$. … Then the method of moments estimate of $\theta$ is? a) 1 b) 2 c) 3 d) 4 The way I approached this question is: The first method of moment is $\bar{X}$ = $\sum X_i/n$ = ($2+1+\sqrt5+\sqrt2)/4 = 1.66$. …

Here are three (somewhat related) questions about the (Generalized) Method of Moments. I have only just today started studying this method. … understand why this equation is different for the Generalized method, compared to the (non-generalized) method of moments. …

In Wikipedia article (https://en.wikipedia.org/wiki/Nonparametric_statistics) about nonparametric statistics there is "Method of moments (statistics) with polynomial probability distributions" listed as … How method of estimation parameters can be non-parametric? Parenthetically, is there any difference between "non-parametric" and "nonparametric"? Which is more common/correct? …

I have been taught that the Method of Moments Approach could be used to obtain estimates of a bivariate regression of the form y = B0 + B1x + u. … Which distribution are these 2 conditions moments of ? I read that the definition of moments of a distribution are expectations of the powers of the random variable. …

Why in "Method of Moments", we equate sample moments to population moments for finding point estimator? Where is the logic behind this? …

Use the method of moments to estimate the parameter $\theta$. …

I am studying method of moments and GMM in the context of econometrics. Can someone explain on intuitive level, what does it mean to match moments? … Method of moments is exactly exploiting this condition. The basic principle of MoM is to choose the parameter estimate so that the corresponding sample moments are also zero. …

I'm looking for some more insights in applying the method of moments for the Logaritmic (or also called Log-Series) distribution. … There is also no literature I can find on applying the method of moments for the Logarithmic distribution. Does anyone have an idea how to apply the method of moments for this distribution? …

Can someone explain to me the difference between method of moments and GMM (general method of moments), their relationship, and when should one or the other be used? …