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1 answer
31 views

Proportion test for subsamples?

I am trying to compare the outcome of two diagnostic tests performed on the same samples. I ran all of my samples once (n=400) and then ran a subset of the 400 a second time (n=85). We are looking for ...
1 vote
1 answer
8 views

Discrepancy of a sample on Latin Hypercube Sampling

I'm currently working on Design of Experiments (DoE) in order to obtain data to, later on, make some FEM simulations. The starting point is: we want to make those simulations (that depends on some ...
0 votes
0 answers
2 views

Goodness of Fit for Comparing Multiple Fractional Logit Models

I'd like to use employ a fractional logit model where my dependent variable is bounded between 0 and 1 and I have two independent variables. For this type of model, I'm unsure, and hoping to get some ...
0 votes
0 answers
2 views

multivariate time series forecasting

I have a dataset of 200,000 rows. Each row contains the song ID, the number of streams today (day_0), the number of streams yesterday (day_1), etc. up to the number of streams 21 days ago (day_21). My ...
1 vote
0 answers
67 views

What are some algorithms that are immune to class imbalance, and what makes them so? [duplicate]

This question is closely similar, however, the answer only speaks about Logistic Regression being one example. I am interested in knowing if there are more algorithms that are not affected (at least ...
1 vote
1 answer
17 views

Background on notation for generative models

In many papers on generative modeling and Bayesian inference in statistics, I come across the following kind of notation, in particular for hierarchical models. For variables $x_1, \dots, x_n$, it ...
1 vote
0 answers
48 views

How to pick a good training set?

From what I understand, my training set should represent the underlying distribution of objects, but what if my local view is not such a good representation? For instance I am working on a cell (i.e ...
1 vote
0 answers
169 views

How to use boolean features to classify, penalising number of features

I have a set of boolean features (n=~2k) to predict a categorical outcome. I have been using decision trees via sklearn successfully. However, for unseen data, there is a cost to assay each feature, ...
1 vote
0 answers
13 views

Classification rule

In classification, is there any difference between MAP (maximum a posteriori) rule, minimum misclassification rule, and the Bayes decision rule. As far as I know, all of the three rules seem to ...
0 votes
0 answers
11 views
+50

Measuring correlation for variables calculated from pairs of observations

Say I have data for the music and film tastes of a set of users $U$ (let's say we have $|U| = 100$ users). Given two users $u_1$ and $u_2$, say I also have two functions $\mathrm{sim}_m(u_1,u_2)$ and $...
1 vote
1 answer
951 views

Levenshtein/Edit Distance as a loss function for sequence transformer models?

Often, the loss function used for a sequence is cross entropy loss between $y_{true}$ and $y_{pred}$ where both are of size $SeqLength \times NumClasses$. When $y_{pred}=y_{true}$ we get the lowest ...
0 votes
0 answers
5 views

Appropriate coding for bipolar Likert scale

For one of my variables, I am measuring affect on a bipolar Likert scale. The question is "how do you feel about the activity?" The range of responses is Worried-slightly worried-neutral-...
10 votes
3 answers
481 views

Examples of distributions with easily solvable quantile functions but hard to solve CDFs

I'm interested in examples of probability distributions where the quantile function $F^{-1}(p)$ exists in closed form or is easy to calculate but where the cumulative distribution function (CDF) $F(x)$...
3 votes
1 answer
4k views
+50

maximizing KL divergence as the objective function

As far as I know, the most common approach to train neural networks is to minimize the KL divergence between the data distribution and the output of the model distribution which results in minimizing ...
0 votes
0 answers
3 views

Need help with propagation of errors

Let $v_i$ and $u_i$ be measured data and noiseless data respectively, where $i \in \{1, \ldots, N\}$ denotes the $i^{th}$ realization of the random variables $v$ and $u$. The random variables $v$ and $...
0 votes
1 answer
18 views

What is this bias called?

People often transfer money from their savings to their checking account when their checking balance drops below a certain amount, for example, 1000 dollars. Let's say you plot the checking account ...
0 votes
2 answers
911 views

How do I measure the variability in time time-series power consumption patterns?

Figure 1: X-axis represents the time (0-23 hours) and Y-axis represents the electricity consumption in kWh. I am working with time-series power consumption data. Figure 1 shows the shapes of one user ...
0 votes
0 answers
4 views

Meaning of asymptotic in the context of stochastic process

So for a fractional Brownian motion, I define $k^{th}$ variation as $$ S_n = \frac{1}{n}\sum_{i = 1}^{n}{|B_{H}(i\times\frac{T}{n}) - B_{H}((i - 1)\times\frac{T}{n})|^k} $$ where T is fixed and $B_H$ ...
0 votes
0 answers
18 views

Does it make sense to include both age and birth year as covariates in a model?

A researcher asked me about adjusting for both age and birth year in a model. To my mind these are perfectly collinear, but then it got me started looking around online and down the rabbit hole of age-...
3 votes
1 answer
562 views

How can I get the cumulant expression from the recursive relation between cumulant and moment?

I am reading some paper about high-order statistics https://link.springer.com/article/10.1007%2Fs11004-009-9258-9?LI=true. The paper gives two recursive expressions relating the multivariate cumulants ...
0 votes
0 answers
5 views

How do I identify participants that are causing low internal consistency?

I have a low cronbach's alpha for one my study's measures (around .6). Half of the measure is reverse coded, and these reverse coded items are the ones that were flagged with having low correlation ...
0 votes
0 answers
7 views

Implications of using a caliper when matching: Would it ruin ATE claim?

I've started to learn about matching methods using MatchIt package, and read "Choosing the causal estimand for propensity score analysis of observational studies" (Greifer & Stuart, 2021)...
0 votes
0 answers
4 views

R – Model specification for TWO TIME variables AND PAIRED design in repeated measures generalised linear mixed model (GLMM) (in lme4 package)?

This question has already been suggested to be reposted here from stackoverflow. I have a dataset similar to below: Fixed effects of interest Hour (4-level factor) Response (continuous) Treatment (2-...
1 vote
0 answers
12 views

Bias adjustment in a transformation - adjustment before and after transforming

Suppose $X\sim(\mu, \sigma^2)$ (I'm happy to also assume normality), and let $Y = h(X)$ where $h$ is at least twice continuously differentiable. I want an approximation of $E(Y) = E[h(X)]$. One ...
0 votes
0 answers
5 views

How do I retrieve the testing and training logloss from a last_fit XGBoost model using tidymodels?

I'm trying to make a plot using the evaluation logs from model training and testing for my XGBoost model (using r) but I can only plot the training evaluation log after performing last_fit (fit to ...
1 vote
1 answer
20 views

Choosing correct statistical tests

I need to come up with the fitting statistical tests for my university and don't know exactly how to approach this problem. Following scenario: In theory entrepreneurs can be divided into 2 groups: ...
4 votes
2 answers
183 views

Does the density $g(y) \propto (1-y^2)^{(n-3)/2} e^{\delta y} \quad\text{for}\quad |y| \leqslant 1$ have a name?

The following probability density function has a particularly simple form, and it was produced when deriving a confidence interval for $\frac{\mu}{\sigma^2}$ , $$g(y;\delta)=c_\delta(1-y^2)^{(n-3)/2}e^...
0 votes
0 answers
9 views

Can I use a likelihood-ratio test when the measure of deviance between two models is not the log-likelihood?

We use the Nelder-Mead optimziation algorithm (as implemented in the dfoptim package for R) to fit a model with several free parameters. What is minimised (in our current implementation) when ...
1 vote
2 answers
609 views

Forecasting with ets: Is my model performing well?

I'm new to forecasting and playing around with some forecasting techniques. I used the ets function from the forecast package to ...
0 votes
1 answer
7 views

Strange output for glmmTMB and pairwise comparison

I am running a glmmTMB to see if there is a significant difference in survival to the eyed egg stage (proportional data between 0 and 1) depending on what genetic male type was used (W, YY, or F1) to ...
4 votes
1 answer
108 views

Uniform prior and poisson likelihood, what posterior distribution will be produced?

If i have a uniform distribution over a fixed specified and a finite range, and a Poisson likelihood distribution, what posterior will be produced? The likelihood has this form $$P(\pmb{X}| \pmb{\...
1 vote
0 answers
255 views

how to test for moderation effects comparing two regression models?

I collected data about consumers website usage behavior and reaction to online advertising for mobile and desktop devices. My goal is to analyze how consumers website usage in reaction to online ...
-1 votes
0 answers
34 views

papers on graduate statistics [closed]

Edited for clarity and details, according to the site. I have some statistics on graduate students (time to finish, number of advisors, and time for them to become researchers). This is in excel ...
2 votes
1 answer
540 views

Interpretation of scaled error measures

can someone give me an explanation on how one would interpret the result of a scaled error measure. For example the Mean Absolute Scaled Measure (MASE). The numerator is the mean absolute error and ...
0 votes
0 answers
34 views

What does this notation mean: $$ \mathcal{N}(0, 7^{3/2} (-\Delta + 49 \mathcal{I})^{-2.5})? $$

Found it in Appendix A3.3 (and A3.2) of this paper: Fourier Neural Operator for Parametric Partial Differential Equations I understand the basic notation of the normal distribution, but this notation ...
1 vote
0 answers
12 views
+100

NER With Custom Tags, How to Approach

I am building a "field tagger" for documents. Basically, a document, in my case something like a proposal or sales quote, would have a bunch of entities scattered throughout it, and we want ...
1 vote
1 answer
137 views

Does it make sense to compare on a dummy model?

Say someone were to construct a binary classifier A on some variables. They want to determine whether those variables help with prediction or not. So they build a second binary classifier which ...
1 vote
0 answers
100 views

Splitting Data Into Training and Test set [closed]

I am trying to split a data set into training and test set with these codes ...
0 votes
0 answers
38 views

Ideas to identify cutoff points for tumor classification?

My lab models breast cancer in mice. I am using a 36-gene signature (derived from one of our mouse models). In the signature, all genes are elevated. I have 997 human samples and would like to apply ...
1 vote
0 answers
26 views

Measure for classification where model predicts a class with a given confidence

I currently have a model which predicts one of four classes and gives a confidence with its output. How can I score my model taking into account the confidence the model should be penalized if a ...
2 votes
1 answer
42 views

What statistical test can I use? If any?

I'm currently investigating mortality rates in my local area compared to England. Mortality rates in my local area have always been higher than England however recently I've noticed a widening gap ...
0 votes
1 answer
240 views

Fitting an ARIMA subset model in R

Suppose I have a time series. After looking at the PACF plot, it largely decreases to zero after 3 lags, but there is also a PACF value that "pokes out" of the significant bounds at a far ...
-1 votes
1 answer
49 views

Usefulness of p-value to flag outliers in a data set

Suppose I have a set of data such that $$y= a\times x + b + \varepsilon $$ I am trying to find $a$ and $b$, but some $y$'s are outliers and up to 80% of the data is missing, so I don't have access to $...
0 votes
1 answer
323 views

Does replacing a random variable in a sum with it expectation shift the mass of the expectation towards the mean?

Assume any two positive, independent random variables $X$, $Y$ with pmf's $f_X$ and $f_Y$, as well as a third (degenerate) random variable $Z$ that is defined to be equal to the expectation of $Y$, i....
1 vote
0 answers
9 views

Comparing alpha and beta diversity metrics between groups in a repeated measures study

I am trying to determine the appropriate tests to analyze my data from a repeated measures study and would greatly appreciate any advice. In this study we took three sample types (small intestine, ...
0 votes
0 answers
18 views

Training an image classifier to detect slight differences in line angles

I've been struggling to find success training a Yolov8 classifier to detect slight difference in line angles. My hunch is that the difference in line angles are so slight that the classifier is ...
0 votes
0 answers
18 views

When conditioning a Gaussian process, why is the conditional mean always trending upwards?

I have a Gaussian vector with mean $\mu$ and covariance matrix $\Sigma$, both estimated. The vector $\mu$ represents a process and for each entry starting with the second, I want to find the ...
5 votes
1 answer
242 views

One Sample T-Test - Data Transformation

I have a dataset ($n=52$) of samples that I would like to test against a known value (e.g., $5$). Because I am testing my population mean against a known mean, this would be a one-sample t-test. My ...
0 votes
0 answers
10 views

Prediction Interval for TLS

I have a set of independent variables $x_i$ and dependent variables $y_i$, both of which have errors $s_{x_i}$ and $s_{y_i}$. So, I use Total Least Squares (TLS) to fit a linear model to my data. I ...
3 votes
1 answer
943 views

Calculating the CACE using instrumental variables

In randomized trials with non-compliance among the treatment group, a common estimator is the Complier Average Causal Effect (also called the Local Average Treatment Effect), which (conditional on a ...

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