All Questions

1
vote
1answer
9 views

Interpretation of interaction term

I have a model: $$ \ln({\rm earnings}) = a+b_1{\rm female}+b_2{\rm white}+b_3{\rm female}\times{\rm white} $$ ${\rm female}$ and ${\rm white}$ are dummy variables. I have interpreted $b_1$ and $b_2$: ...
0
votes
0answers
3 views

estimate missing values in unbalanced design

I want to estimate the NA values of the table. ...
1
vote
0answers
7 views

Fitting multiple models to a noisy measurement

I have measured a quantity for a set of data contains couple of thousands objects. Since the measurement is very noisy, I need a set of data contains a lot of objects. Then I have a model based on the ...
0
votes
0answers
6 views

r-pnn, normalization and different distance measures for each variable

Since pnn is a NN that uses a Radial kernel to classify data, I think the distance measure is key and, in consequence, the normalization of the data. Am I right? How does pnn package calculate the ...
0
votes
2answers
11 views

Testing equality of two X values in quadratic regression

So let's say we have a quadratic relationship between two variables, y and x. Graphically, it is U-shaped. However, there is also a linear component to it, such that the left curve is lower than the ...
0
votes
0answers
11 views

Bayes nets - calculating probabilities

Given a Bayesian network, say a -> b -> c, all binary random variables (I won't show the CPTs, assume they are given). You are told b and c are true. How do you calculate the P(a=True)?
-1
votes
0answers
15 views

Given some nodes in a Bayes net, what is the probability of another node being true?

By example: Say LC = False, MP = True. What is the probability of CG being true then?
0
votes
0answers
9 views

How to test heteroskedasticity at the independent variable level?

I know how to test the heteroskedasticity of a model's residuals. I am inquiring about how to test for heteroskedasticity for each specific independent variables included in the model. What is the ...
0
votes
0answers
14 views

Add a quadratic random effect to a nonlinear mixed model?

How can one add a quadratic random effect to a nonlinear mixed effect model? I've been trying to do this with nlmer without luck. Any tips would be greatly appreciated! Here's my starting point that ...
1
vote
0answers
10 views

Risk in density estimation: grasping the definition

When generalizing estimators to an entire function what is the space in which we perform the integral to obtain the expected value (with respect to this function)? For example, when estimating ...
0
votes
0answers
7 views

Use Profile Hidden Markov Models in Bioinformatics

If I have new DNA sequence and want to use profile HMM for alignment, What the steps I should to follow with details please?
0
votes
0answers
6 views

On computing the Wolfe's t-Test

I have a sample with $n=1000$ subjects. For each subject I have three variables measured, let's say $X$, $Y$ and $Z$. I have the following correlations: $r_{xz}$ = 0.80 $r_{yz}$ = 0.83 I want to ...
0
votes
0answers
11 views

Sample size calculation for non-normal data (possibly lognormal)

I am currently trying to rack my brains to find a solution but I seem to be coming up with nothing. I have water quality data with which I want to get a sample size calculation from for a future ...
0
votes
0answers
4 views

AIC or similar selection techniques for Variograms?

I have a very basic question: how does one choose the "best" variogram? It is possible to fit different models to an empirical variogram, e.g. nugget, ...
2
votes
0answers
17 views

Methods of fitting a dynamic linear model

I'm taking a time series course and am learning about exchangeable time series form of dynamic linear models (DLMs). This is given by: \begin{align*} \mathbf{y}_t' &= ...
4
votes
3answers
82 views

What is the best way to remember the difference between sensitivity, specificity, precision, accuracy, and recall?

Despite having seen these terms 502847894789 times, I cannot for the life of me remember the difference between sensitivity, specificity, precision, accuracy, and recall. They're pretty simple ...
2
votes
0answers
16 views

Is there any use of having dual error bars in bar charts to show both descriptive and inferential statistics?

I would like to display information both about the distribution of the population and the certainty in the measurements in the same plot. Would there be any use of having dual error bars in a barchart ...
2
votes
0answers
15 views

Why do the estimated values from a Best Linear Unbiased Predictor (BLUP) differ from a Best Linear Unbiased Estimator (BLUE)?

I understand that the difference between the is related to whether the grouping variable in the model is estimated as a fixed or random effect, but it's not clear to me why they are not the same (if ...
0
votes
0answers
5 views

Confidence interval on replicates from multinomial distribution with bimodal outcomes

I have a Java model which tracks the numbers of 6 types (A-F) of individuals. I am interested in the distribution of different types of individual across simulations with different parameter values. ...
2
votes
0answers
20 views

Latent Class Analysis vs. Cluster Analysis - differences in inferences?

What are the differences in inferences that can be made from a latent class analysis (LCA) versus a cluster analysis? Is it correct that a LCA assumes an underlying latent variable that gives rise to ...
1
vote
1answer
23 views

Logistic Regression using fractional polynomials in R

I have been developing a model based on trauma data of head injury in the UK. The key outcome is 30 day mortality (denoted as "Survival" measure). In a dataset of 2134 patients, there are other ...
3
votes
2answers
20 views

Cointegration - Why can't I estimate a VAR on the differences?

When talking about variables that are I(1) (the first difference is stationary), Lutkepohl book says: "...in general, a VAR process with cointegrated variables does not admit a pure VAR representation ...
1
vote
1answer
25 views

expressing a discrete distribution as a mixture of bernoullis

How would one express a discrete distribution as a probabilistic mixture of Bernoulli random variables? An example of a discrete distribution being something like this: $P(X=1)=0.15$, $P(X=2)=0.45$, ...
0
votes
0answers
19 views

Factor analysis with categorical reponses and missing data

I factor analyzing a measure with 55 categorical items (3 categories each). I am use CFA to test a 7 factor model. I have a very large sample (>10,000), but approximately 20% of the sample is missing ...
2
votes
0answers
17 views

nonlinear meta-regression

Can someone point me to a basic explanation of theory and methods for fitting nonlinear curves (particularly quadratic functions) to meta-analytic data? I have a set of effect sizes that are clearly ...
0
votes
0answers
4 views

Do the marginalised posterior and likelihood function converge in the limit of a large number of observations

Short question Do the likelihood function evaluated at the ML estimate and the marginalised posterior converge in the limit of a large number of observations? Long question I expect the two ...
0
votes
1answer
30 views

Repeated measures ANOVA and uneven number of trials

Suppose I have multiple responses from each subject in three different conditions (A, B, C). If I would decide to run a repeated measures ANOVA, I would first average over the repetitions from each ...
2
votes
2answers
39 views

What are desirable characteristics of a test statistics?

I've seen definitions of statistics which combine multiple terms in a very specific way. What are advantages of these expression and why not use just any calculation on the data? For example why do ...
1
vote
1answer
40 views

What are the implications of estimating a covariance matrix from a correlated sample?

Given a sample of $n$ independent observations $x_1,...,x_n$ (where $x_i$ are $p$-dimensional column vectors), the $p \times p$ sample covariance matrix is defined as ...
1
vote
0answers
21 views

Sum of RV : probability for the value of operands when the result is known

A random variable $Z$ is the sum of two independent random variables $X$ and $Y$, with known probability densities $f_X$ and $f_Y$, respectively. Now suppose you sample $Z_1=X_1+Y_1$ but you don't ...
0
votes
0answers
7 views

Choosing or determining the degree of regularization for effective degrees of freedom

I have a model of the form $Y=f(X,\beta)+\epsilon$ and from The Elements of Statistical Learning, I see that one can use an effective degrees of freedom, defined: $$ {\rm df} = \sum_i ...
0
votes
0answers
19 views

Propensity score to match on exposure thats not a treatment

I have two questions on this subject: (1) The literature on propensity score (PS) consistently discusses the ability of PS to balance groups with different treatments. Does PS allow for balancing on ...
1
vote
0answers
25 views

How to do cross-validation when comparing different feature selection methods?

I am using SVM for a prediction task. My sample size is small, only N=140. Suppose I want to compare the prediction accuracy when using two different feature selection methods. Would it be better to: ...
0
votes
0answers
13 views

Plot connections between researchers based on publications

I would like to plot how researchers from my university are connected with other researchers worldwide and see how these connections evolved as a function of time. My idea to do so is to start from ...
0
votes
0answers
28 views

New research ideas [on hold]

I am pursuing a project on Tracking learning and detection in a video stream. For that, I have read the paper titled Tracking-Learning-Detection. But as this paper was written in 2011, most of the ...
0
votes
1answer
18 views

Degree of belief in fuzzy modelling

I’ was reading a paper on fuzzy regression. In that paper, and many other papers on fuzzy regression, the authors use most of the time a $h$ to indicate a certain degree of belief. Unfortunately the ...
1
vote
1answer
32 views

MANOVA when sample size is smaller than the number of DVs

I need to compare $16$ quantitative variables, measured for two groups, A and B. I thought of applying MANOVA. However, there are only $4$ and $9$ cases for groups A and B respectively. I looked for ...
1
vote
2answers
81 views

How can I get more precise regression tree?

I am a complete newbie to regression trees so maybe I am not understanding it properly. I got the following tree from my analysis (function tree() from R package ...
0
votes
0answers
37 views

When normalization is counter-productive

Could you give me general examples of when normalization is not used properly and affects badly the classification accuracy, or when it is not needed?
0
votes
1answer
14 views

quantile regression with e.g. gamma distribution and log link

I have a basic question about quantile regression (I'm new to it): Why doesn't it seem possible to do a quantile regression with a specified family (e.g. gamma) and link function (e.g. log), as in a ...
0
votes
0answers
9 views

Including non-linearity to the first difference

I have an issue running the First diffeerence estimation. After running it with all the controls I got a really low RESET test, and thus would like to add a non linear term to my model. In order to do ...
0
votes
0answers
5 views

GAM-style effects plots for interpreting qrnn model

how to analyse GAM-style effects plots for interpreting qrnn models. I couldn't quite understand it from R documentation.
0
votes
0answers
14 views

How to make beta coefficients comparable?

My study design delivers both, count data and continous outcomes (e.g., numbers of taxa vs. an diversity index). As these variables are used as response variables, I have to use negative binomial glm ...
0
votes
1answer
12 views

What is Median Error Distance and how to calucalte it

How to calculate Median Error Distance? I'm looking at "Schulz A. et al. A Multi-Indicator Approach for Geolocalization of Tweets". They are calculating Median Error Distance. But how they are do ...
0
votes
0answers
10 views

Compute Transition Matrix

I am studying Markov Chain. I want to compute transition matrix. Is this the right way to do it ...
0
votes
1answer
13 views

Proportion Comparison

I have data from baseline and end line surveys. Baseline was conducted before intervention in children and end-line was conducted after intervention in the same population. Study population is same ...
1
vote
0answers
17 views

Least Squares Estimation of Poisson Parameter

"Assume independent random variables $Y_i$~$Poisson(λx_i)$. Supposing that $x_i$ are given, fixed constants, obtain the least squares estimator of $λ$ and compute its variance." This kind of a ...
1
vote
0answers
20 views

MLE == MAP under Uniform Prior? [duplicate]

Does Maximum Likelihood Estimation always yield the same result as Maximum a Posteriori with uniform prior?
0
votes
0answers
5 views

Event level driven response modeling

I am investigating operational and maintenance data for a fielded system. There is a year worth of data. The operational data has been reduced to fault indications, which are triggered when ...
2
votes
2answers
28 views

Name for outer product of gradient approximation of Hessian

Is there a name for approximating the Hessian as the outer product of the gradient with itself? If one is approximating the Hessian of the log-loss, then the outer product of the gradient with itself ...

15 30 50 per page