Questions tagged [estimators]

A rule for calculating an estimate of a given quantity based on observed data [Wikipedia].

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985 views

Why don't asymptotically consistent estimators have zero variance at infinity?

I know that the statement in question is wrong because estimators cannot have asymptotic variances that are lower than the Cramer-Rao bound. However, if asymptotic consistence means that an estimator ...
1k views

What are the main different/alternative correlation estimators?

I'm looking to learn about the main/popular alternatives when it comes to estimating correlations that I've missed in the following list. The best answer will provide a reference (can be Wikipedia), a ...
49 views

Partitioned regression model: estimator of beta 1

below is an exercise that is really giving me a hard time, I believe that there is a simple way around it but I can not find it: Assume the correct regression model is Y = X$\beta$ + $\epsilon$ for E(...
55 views

Rank forecasting from uneven samples

Say we have a bag of chocolate balls. There are $I$ different unique colors. Our bag has an unknown number of balls for each color. We want to get a sense of which color people like the most and ...
557 views

MSE of an individual coefficient from ridge or lasso vs. OLS

Consider a multiple regression model $$y = X\beta + \varepsilon$$ with $K$ regressors in $X$. If the model is correctly specified, the OLS estimator $\hat\beta_{OLS}=(X'X)^{-1}X'y$ will be the ...
61 views

Estimating the mean with least median of squares

I have a set of real numbers $x_{1}...x_{n}$ and would like to estimate their mean (let's call it y) so that $median(x_{i}-y)^{2}$ is minimal. Is there an algorithm and a correctness proof for ...
68 views

Forming an unbiased estimator of the maximum of several parameters, given independent estimators of each parameter?

Say I have $K$ independent normals, $X_i \sim \mathcal{N}(\mu_i, \sigma_i)$ for $i = 1,...,K$. How can I form an unbiased estimator of $\max_i \mu_i$ using $X_i$'s?
42 views

Mean Squared Error as quantifier of the Bias-Variance tradeoff

I have acquired the impression that many of the people doing statistical work, will prefer a biased estimator $\hat b$ to an unbiased one $\hat \beta$, if the former has lower Mean Squared Error. This ...
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Trying to understand an example where unbiased estimators don't exist

I am new to statistics especially in the topic of estimators and sufficient statistic. I am reading a note which says "unbiasedness is a desirable (but not necessary) property of a good estimator". ...
250 views

Quantile regression analyzing the conditional quantiles of one of the regressors?

Given response $Y_t$ and predictor $X_t$, we can use OLS to analyze the conditional mean; $E[Y_t | X]$. Quantile regression can be used to analyze the conditional quantile function; $Q(Y_t(\tau)|X)$. ...
29 views

Parameter estimation by averaging over all high-likelihood possibilities?

I am refereeing a chemistry paper. The authors are trying to interpret some experimental data by comparison with numerical simulations. They have run many simulations using different combinations of ...
24 views

variance estimator for a symmetrical two-sides censored normal distribution

Suppose to draw a sample of $n$ observations from $X \sim \mathcal{N}(0,\sigma)$, with observations outside the interval $(-c,+c)$ censored; $c$ is known and one can conveniently set $c=1$, for ...
48 views

Best way to estimate the probabilities of a random variable

I have some confusion about estimating the probability of a particular value of a random variable. For simplicity, consider the case of a coin and the random variable being $X = \{H,T\}$, where $T$ is ...
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Statistical theory proof intuition (UMVU estimators)

I've been working through this problem in Theoretical Statistics by Keener, but could not solve it. I looked up the answer and I do understand why it's correct, but I don't understand what intuition ...
33 views

When you see an item twice for the first time during k random choices, the total number of items is ~ k² / 2

Let $X_1, X_2, ..., X_k, ...$ be a sequence of i.i.d. random variables with $X_i \sim \mathcal{U}\{1, 2, ..., n\}$ (discrete uniform distribution). The parameter $n$ is unknown. Let's say the first ...
34 views

How to get an estimator from this heuristic argument?

In the answer of this question, a practical solution was suggested for: Let $X_1, X_2, ..., X_k$ be a sequence of i.i.d. random variables with $X_i \sim \mathcal{U}\{1, 2, ..., n\}$ (discrete ...
206 views

Comepare two Theil-Sen estimators for significance

Since an ANCOVA was not possible with my data, I moved on to use Mann-Kenndall as well as Theil-Sen estimators to analyze my data. I have three datasets. For two of them Sen's slopes were found to be ...
57 views

Comparing methods of aggregating standard deviations

Background Problem One of the economic/finance software systems that I am using is adopting the following approach to aggregate standard deviations: Let $R_t$ be the time series of interest. The ...
82 views

Can we improve on the sample mean as an estimator of the true mean of a Pareto distribution, 1 < α < 2?

Suppose I have a sample drawn from a population which is approximately distributed i.i.d. according to the Pareto distribution for values of x greater than X*. Suppose, moreover, that the tail index 1 ...
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Sample mean lognormal variables

Suppose you've got $x_1, ..., x_n$ independant realisation drawn from a $LogNormal(\mu, \sigma^2)$. Could someone explain me why $exp(\mu + 0.5*\sigma^2)$ $\neq$ $\frac{1}{n}(x_1 + ... + x_n)$ ? Here ...
42 views

How does the TraMiner Package Calculate Standard Error Using Weighted Data?

The TraMiner Package includes an option to include sampling weights in the analysis. However, I haven't found any discussion in the package documentation (or associated user manual) of how standard ...
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How I can sketch the proof of consistency of only one beta in multiple regression?

Now assume you additionally obtained data on average parental incomes (PI) and the ethnic composition (EC) of the pupils in school. You regress the score on STR PI EC and a constant. State the ...
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Definition of curvature

Kay (Fundamentals of Statistical Signal Processing) defines the curvature of a log-likelihood function to be the "negative of the second derivative of the logarithm of the likelihood function at its ...
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Spherical error variance in OLS estimation of AR($p$)

Consider the linear model $\boldsymbol y=\boldsymbol X\beta+\boldsymbol\varepsilon$. One of the assumptions for the OLS estimator is the spherical error variance assumption which states that \$\...
26 views

Existence of Huber M-estimators

I am working on a paper about optimization using the Huber's Loss function, which is defined as: \psi(x)=\begin{cases} \frac{x^2}{2\gamma},& \text{if } \lvert x\rvert\leq\gamma\\ ...
124 views

Consistency vs. Asymptotic Efficiency of estimator

I'm thinking about the relationship between an asymptotically efficient estimator and a consistent estimator, and I'd like to make sure that my thinking is correct. An estimator is asymptotically ...