All Questions

I have an experiment with two equally sized groups. These groups contain machines and the metric being measured is the failure rate of the of the groups. In a typical experiment setting, the test ...

Including too few variables in OLS regression means that the coefficient estimates can be biased, e.g. if we aren't controlling for a variable in a model that should be there, it is instead captured ...

In deep Q learning, we execute the algorithm for each episode, and for each step within an episode, we take an action and record a reward. I have a situation where my action is 2-tuple $a=(a_1,a_2)$. ...

Say if we had a case: $y=α+βmale+βeduc+ε$ $y=α+βmale+βeduc+βmale*educ+ε$ let's say that both male and educ are indicator variables. What exactly does the interactive term mean in plain English, ...

I have a pandas Dataframe, which has data as structured below. ...

The positive semi-definite concept can be extended to any complex matrix $A$, complex matrix $A$ is called positive semi-definite if $Re[x^*Ax]\ge 0$ where $x\in\mathbb{C}^n$ is any nonzero complex ...

So I am having an issue where all coefficients are at 0. I am trying to find the factors that explain the S&P 500 returns. In my lasso model outcome variable $Y$ is the monthly returns of the ...

I have an 18x25 contingency matrix, rows are behaviors observed and columns are environmental features. I conducted a correspondence analysis via the CA() function in R and then clustered using the ...

So I'm writing my own implementation of AdaBoost using chapter 10 of Elements of Statistical Learning. The pseudocode given in the book lists how to make the algorithm for a classification problem, ...

If $Y = \ln(X)$ and $P(Y) = 0.55$ Can i say that $P(X) = e^{P(Y)} = e^{0.55}$ ? ($P(Y)$ is the probability of $Y$, and $P(X)$ is the probability of $X$)

I am reading a paper and in the methods section of the supplementary material, they describe how they compared the two conditions (stimulated and unstimulated) by saying. Statistical analysis of ...

Given data $(\textbf{X,Y})$, a Gaussian Process $\textbf{F}$ that is normally distributed and weights $\textbf{W}_1$ and $\textbf{b}$ also from a distribution, how come is the following distribution \...

Let's assume we have a multilayer feedforward network with one hidden layer. The hidden layer must consist of at least two neurons with logistic activation function. How many hidden neurons are ...

I am looking at a very interesting time series dataset for the volume of water flow through some groundwater sensors. Our goal is longer term prediction of water levels, such as 1 - 5 years in the ...

For example in that case, all confidence intervals are negative BUT the sum is in positive range (-37.62 to 0.5), which I don't understand. If there is anybody knows the explanation I would be ...

Building a pairwise ranking model using linear algorithms is easy to understand. We just need to do pairwise transformation on the original data and create 0/1 labels. Then feed these pairwise ...

I have a couple of datasets that contain results of tests, saying whether or not they have a disease. For those that are infectious, I have test results of children in their households. From this, I ...

Thank you for looking at my question, I've been driving myself a little crazy over it today! I have run tests for the assumption of homoscedasicity however I have been deliberating whether the ...

I just started thinking of an experiment where stimuli change according to two variables: eg., color and shape. Let's suppose that there are two objects presented one after the other (Obj 1 and Obj ...

I'm learning by building models on UCI datasets and I've found interesting and difficult (for me ;-)) dataset I'd like to build 6 regression models (or use multivariable regression) and find out ...

I am currently working on an empirical analysis in R. To give you some background information: I want to estimate a VAR-model to subsequently develop IRFs from it (using cholesky decomposition). My ...

I have a time-lagged, multi-step conversion funnel. For simplicity, lets assume it looks like this: Lead submit ----> Lead contact ----> Lead convert Where ...

Given some discrete random variable $X$ with pmf $P(X)$ the expectation of its negative log probability $H(X) = E_{X}[-log(P(X))]$ is defined as the entropy which is an important statistical quantity. ...

What topics should I read on to prepare myself for data extraction from invoices (in image file or PDF). Basically I will have a file with invoice and need to extract from it such information as ...

Let $$ f(x) = \sqrt{1-x^2}, \quad I = \int \limits_0^1 f(x) dx. $$ We consider the following estimator of I: $$ \hat{I}_n = \frac{1}{n} \sum \limits_{i=1}^n f(X_i), $$ where $X_1, X_2, ...$ are iid $...

I am new to BI and its core programms. As in the past I manually downloaded report-files, clear them out and adjust data I was looking for a way to automate this and heared about Power-Qurey for Excel ...

I am performing an ANOVA to compare the means of three groups. However, I need to adjust for the effects of age and gender in the ANOVA. I'm not quite sure how to go about it in R. Conventionally, I ...

I'm trying to forecast daily data (I have 15 years of historical data) with complex seasonality: weekly, monthly, annual and also irregular seasonality due to moving events like Easter. As suggested ...

Has anybody an experience with MANCOVA - TYPE 3? I've usually used the function "mancova" (package jmv), but there is not possible to change the settings and the result is always "type 1". Does ...

We have done a bunch of measurements of air speed in function of pressure drop for different stack configurations. Stack configurations entail: the number of films in the stack (known) the distance ...

I am trying my first LSTM with keras to classify time-dependent data sets. I have created a training and a testing data sets, which I have normalized: ...

I'm trying to use GLMM in R to fit a mixed-effects model (3 categorical predictors, 1 continuous predictor) to trial-level reaction times from a group of participants. The reaction time ...

I am trying to build an LSTM model to predict temperature for a given day using say past 7 days of temperature, rainfall etc of a Zipcode or PinCode. I understand that the training dataset needs to be ...

I hope this message will find you well My main question would be : were to focus ? And for you to be able to answer that, I should give you some informations, both on where I am, and where I'd like ...

I'd like to perform a mediation analysis in Python and have done the following so far. ...

I have the following ranges as GRanges data {Ranges_1}: 1-2, 2-4, 3-6, 6-8, 2-8, 8-11. {Ranges_2} 1-5, 6-10, 11-15, I need a mapping from Ranges_1 to Ranges_2. Something like following (1-2) -> (1-...

A loss distribution has PDF - $f(x) = 1/x^2$, for $x > 1$ An insurer finds that the time in hours it takes to process a loss amount x has a uniform distribution on the interval $(\sqrt x, 2\sqrt x)$...

I wanted to ask about anova F-test. Can this test be used to measure coefficients contribution on dependent variable? Anova test compares variations between and within a certain groups and in linear ...

My QQ-plot indicates normality (a fairly straight line), but my density plot shows departures from normality. Why is this happening? Is this a big problem for my model? Here's my model syntax: <...

I have two quantitative traits coming from 145 individuals x 12 environments combination. My goal is to correlate the specialization of each individual (trait 1) to the mean of each individual across ...

Take any $({\lambda},{\mu},F,G)$ such that 1) $\lambda\equiv (\lambda_1,..., \lambda_J)$, $\lambda_j\in (0,1)$ for each $j=1,...,J$ and $\sum_{j=1}^J \lambda_j=1$ 2) $\mu\equiv (\mu_1,..., \mu_J)$ ...

I have one continuous independent variable weight and one categorical binary independent variable gender. Gender is a binary column consisting of 0 and 1.From the linear model summary below my ...

I am trying to understand the link between the threshold in ROC-analysis and the threshold defined in classification table. Criterion is binary with 0 or 1. 1) Someone can determine a confusion ...

I want to subtract the mean from my time series. Each data point has a corresponding errorbar. I calculate the mean by fitting a constant with a MLE estimation and estimate the standard error with the ...

I have data for people who participated in a randomised clinical trial. Approximately half received a lifestyle intervention, the others received nothing. Measurements of the ...

I'm new to lme4, so apologies for the simple question. I have the following variables: W: within-subject (categorical: a, b, c, d, e, f, or g) B: between-subject (x or y) age: observed (continuous) ...

I am reading Eilers and Marx (1996) and at the beginning of page 94 they write, for $Q = B^TWB$, $D$ a symmetric positive definite matrix and $W$ a diagonal matrix, \begin{align} tr\left(B(Q + D)^{-1}...

I have an hourly forecast (let's say it's for rainfall) projected for 40 years. I am using this forecast to plan an activity (for example: outdoor construction; you don't want to plan to be working ...

I have a network where nodes are labelled in two classes "a" and "b". I want to measure how connected these two groups are and I looked at assortativity by group. I want to use this measure in more ...

I am starting to work in data science and machine learning and I have a little question. I am trying to construct a model that predict a continuous variable, it means, a regression model. I have nine ...