# Questions tagged [estimation]

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### Parameter estimation for basis function model in Elements of Statistical Learning (ESL)

In the book Elements of Statistical Learning, section 2.8.3 describes Basis Functions, citing an example of a radial basis function as $f_{\theta}(x) = \sum_{m=1}^M \beta_M \sigma(\alpha_m'x + b_m)$, ...
31 views

### Estimating Joint Probabilities from Marginal Probabilities

Given 2 categorical variables and their marginal probabilities of variable C. What is a good simple way of estimating the joint probabilities? Let C be a Boolean T/F survey variable. For example: ...
6 views

### what metrics to use to estimate accuracy of range prediction?

I trained a model that predicts customer's income given the features: age, declared income , overdue total amount active credit limit, total credit limit Metrics used: NIRDM - not in range distance ...
19 views

### VAR($p$) estimation

I am bit stumped by this result. Source: Remark on page 46 of Multivariate Time Series Analysis by Rsay. ... one can obtain the GLS estimate of a VAR($p$) model equation by equation. That is, one can ...
32 views

### Monte Carlo standard error for a sum

Suppose that I want to compute $E[X+Y]$ using Monte Carlo simulation and compute the standard error. (Note: $X,Y$ are not necessarily independent) The standard way to do this is to Consider the ...
2 views

### relationship between the confusion matrix of a detector and the variance of an estimator

Say I have a detector with a confusion matrix. Also, I am interested in the estimation of the number of the detected cases $(\hat{N})$ rather than in the parameters given by the confusion matrix. For ...
29 views

### Question about estimating the standard error of the regression- notation and intuition

in a standard linear regression frame work: $y_{i}=\beta x_i + \epsilon_i$ when calculating standard errors, we find an unbiased and consistent estimator of $var(\hat{\beta})$. Assume spherical errors....
23 views

### While simulating the value of a double integral , why do we need to draw different samples everytime?

Suppose I want to simulate the value of the integral $\int_{0}^{1} \int_{2}^{3} 2xy \ dx dy$ using Monte Carlo methods. So, now, I draw a random sample from $U_1,U_2,...,U_n$ from $U(0,1)$ and for ...