# Tagged Questions

The difference between the expected value of a parameter estimator & the true value of the parameter. Do NOT use this tag to refer to the [bias-term] / [bias-node] (ie the [intercept]).

3 views

### Systematic sampling and informed consent: Does the requirement for informed consent introduce sampling bias into randomly selected samples

Probability sampling methods help reduce sampling bias. In clinical research, simple random sampling methods works well for randomised control trials, and systematic sampling methods are easy to ...
19 views

### A linear learner has high bias, because when the frontier between two classes is not a hyperplane the learner is unable to induce it

Can someone explain to me what this sentence means: A linear learner has high bias, because when the frontier between two classes is not a hyperplane the learner is unable to induce it. The ...
16 views

### Coefficient bias in ARIMA vs. lagged regression

I am trying to estimate the effect of an external regressor $x_t$ on a time series $y_t$. My first attempt was using an ARIMAX(p,d,q) Model to estimate $\beta_x$ while controlling for the ARMA ...
34 views

### Noisy (and biased) MCMC?

When estimating intractable expectations using MCMC, we usually assume we can evaluate the (unnormalized) target density exactly at any point. I.e. we're interested in evaluating expectations w.r.t. ...
40 views

### Why does RMSE underestimate model variance?

I have read that RMSE of calibration/validation/cross validation is frequently used for model selection (e.g., for ANN), but can lead to over-fitting because the prediction error represents the ...
16 views

### How to asset bias in data used to update a recommender systems?

I want to study the bias in a recommender systems.So,in each iteration,the recommender systems update the model using the coming data(new ratings) from users.and then, the RS recommend a top N items ...
71 views

### Difference in expressions of variance and bias between MSE and MSPE

The difference between Mean Square Error (MSE) and Mean Square Predicted Error (MSPE) is not the mathematical expression, as @David Robinson writes here. MSE measures the quality of an estimator, ...
80 views

### What's the difference between asymptotic unbiasedness and consistency?

Does each imply the other? If not, does one imply the other? Why/why not? This issue came up in response to a comment on an answer I posted here. Although google searching the relevant terms didn't ...
19 views

### Is it possible to correct for bias in the tetrachoric correlations of rare events in small samples?

Background and Problem I am developing a meta-analytic epidemiological model to predict the prevalence of a series of related psychiatric disorders. As part of the modelling process, I need to ...
421 views

### Bias of moment estimator of lognormal distribution

I am doing some numerical experiment that consists in sampling a lognormal distribution $X\sim\mathcal{LN}(\mu, \sigma)$, and trying to estimate the moments $\mathbb{E}[X^n]$ by two methods: Looking ...
14 views

### Consistent estimation with observed values lower than actual values

Assume an IID sample of the form $\left\{ y^{r}_{i},\mathbf{x}_{i} \right\}$ (notice the superscript on $y$). The observed values $y^{r}_{i}$ are bounded from above by the actual, unobserved values ...
18 views

### Principal Coordinates Analysis (PCoA) with Longitudinal Data

I am interested in running a PCoA on a distance matrix derived from longitudinal data. I'm concerned about biasing the PCoA towards overrepresented subjects (those with more time-points and samples). ...
41 views

### Autoencoder with tied weights: bias?

For some unsupervised learning problem, I need to train an autoencoder, so that I only have to store the encoder afterwards. However, I am not sure on how and if the bias weights can be tied. To make ...
35 views

### Finding the MSE Using the Delta Method

I don't get the step in the solution for b) can someone please fill in the missing steps between going from eqn (1) to the solution. Thanks. Question: Solution:
35 views

### Does increasing sample size have any effect on omitted variable bias?

Say I have a multiple linear regression model, where two of the variables are positively correlated, and I omit one of these variables from the model. First question - if I increase the sample size, ...
155 views

### Something wrong with my implementation of the bias/variance diagnostic in polynomial regression

I'm trying to diagnosing bias/variance so I have the below Octavecode: ...
36 views

### Why is are unbiased statistics used more commonly than statistics with lower MSE?

I understand the difference between consistency and bias; one converges as the sample size increases, and the other converges as the number of estimates increases, respectively. But, I don't ...
9 views

### When on the same data and model an unbiased estimator and a biased estimator give similar values

There was a general consensus here that statements like I calculated Observed $R^2$ and Adjusted $R^2$, and they were pretty similar, suggesting only a small amount of bias in the Observed $R^2$ ...
51 views

### Heteroscedasticity and bias shown in residual plots, lme

I have been fitting a linear mixed-effect model. The residual plots are not desirable. I have found many posts telling me the first is heteroscedastic, and the second is biased. But I can't find info ...
21 views

### Bias of sample correlation for discrete distributions

Is there a proof showing the bias (or lack thereof) of the sample Pearson's correlation for discrete interval variables? In particular, I am interested in how such a proof handles the expected value ...
84 views

### Overspecification bias/ including too many variables to a regression model

This seems to be the general view in statistics community: If the regression model is overspecified (outcome 4), then the regression equation contains one or more redundant predictor variables....
8 views

150 views