All Questions

0
votes
1answer
36 views

In marketing experiment, can we determine the effect customer state has on response?

We have the goal of determining whether an email campaign has an impact on the amount of product that customers purchase. We have customers from several states but much more from some states than ...
0
votes
0answers
12 views

what is the simplest algorithm of trial and error strategy? [on hold]

I want to implement a simple trial and error algorithm to control an event by chechking after every operation if a set of input parameters change or not. I know that Reinforcement learning ...
5
votes
1answer
146 views

Likelihood modification in Metropolis Hastings ratio for transformed parameter

I want to use MH to get samples from $p(\theta \mid y) \approx p(y \mid \theta) p(\theta)$. Let's assume $\theta$ is heavily constrained and I transform $\theta$ to $f(\theta)$ so I can sample from ...
0
votes
1answer
22 views

Dealing with a binomial outcome, is it correct to apply Mixed Logistic Regression in order to analyze plant's seed viability?

I've been reading several questions asked in this website but I couldn't quite find the answer that I'm looking for. It seems that my experimental design it's not that typical. It goes like this: I ...
0
votes
0answers
10 views

Notation question for multiplying matrix rows by vector

I have a matrix A and row vector b such that; $A=\begin{bmatrix} a_{11} & a_{12} & a_{13} & \dots & a_{1n} \\ a_{21} & a_{22} & a_{23} & \dots & a_{2n} \\ ...
0
votes
0answers
25 views

Book “introduction to probability 2nd edition” example 1.25 “Grade of Service”, I can't get same result

I am in self-study probability theory. I wrote a python script to calculate $p(15)$ in example 1.25 and got a result '0.05012925454322169' which is '0.0399' in this book. Here is the example: An ...
1
vote
1answer
17 views

cross entropy loss max value

The cross entropy loss function for multiclass can be computed as: $$-\sum\limits_{i=1}^N y_i log \hat{y}_i$$ where $y_i$ is a class and $\hat{y}_i$ the estimated probability. The minimum value is $0$ ...
0
votes
1answer
60 views

My Neural Net can overfit but not generalize

I have created a Neural network that gets its training data from a complicated physics simulation. I run the simulation by randomizing 7 different inputs. Each input can be 1 of 4 discrete values. I ...
0
votes
1answer
14 views

Expectation of multivariate gaussian w.r.t. other multivariate gaussian

I want to calculate the Kullbach Leibler Divergence of two multivariate Gaussians as in KL divergence between two multivariate Gaussians. At one point one has to solve the following expression (...
0
votes
0answers
14 views

binomial pairs probability

A group of four people is said to be “interesting", if there are at most five pairs who are friends. Assume that each pair of people are friends, independent of every other pair, with probability 1/2 ....
0
votes
0answers
15 views

Circular smooths within a GAM-GEE framework

I have a predictor variable which I fit in a GAM as a circular smooth term: ...
0
votes
0answers
7 views

How much time is needed between measures for test-retest reliability?

I am planning a meta-analysis on reliability of various loneliness scales. We want to determine beforehand what time frame between measures we will consider. For instance, if the time between 2 ...
0
votes
0answers
7 views

R | Read linewise from zipped csv File [on hold]

I have a large .csv file zipped into a standard .zip file. As the file is rather large I need to somehow read it chunkwise. I found a solution for a .bz2 file for the same situation here: https://...
0
votes
0answers
17 views

bootstrap standard errors - the mean is equal to the observed statistic?

My question revolves around the accuracy of a estimator which is obtained with bootstrap. This example is taken from "An introduction to bootstrap" Efron & Gong: A small experiment, in which 7 ...
0
votes
0answers
25 views

proof related to gamma distribution function [on hold]

Finding gamma distribution from the given probability distribution function as shown in this picture. A random variable x is said to be gamma-distributed with index α if its probability density ...
1
vote
1answer
16 views

Regarding pre-processing function StandardScaler in scikit-learn library. How to save the scaler variable for predicting new data [on hold]

Please help me. I am trying to give maximum information related to my query. I have a query regarding pre-processing function in scikit-learn library. My data set are divided into 3 parts train, test,...
2
votes
1answer
44 views

Simplification of an expectation

While attempting to simplify a combination of expectations, I'm stuck at a particular term whose simplification I'm unable to deduce. The term to be simplified is: $\mathbb{E}[X^{T}F^{T}FX]$ where $...
2
votes
2answers
17 views

Binary dependent variable sem [on hold]

I need to test a framework and I was planing to apply SEM. My dependent variable is binary, as most of the explanatory (some are also categorical, and few continuous). Witch package/tool do you ...
2
votes
1answer
24 views

Expectation of Sufficient Statistic

Consider $X \sim B(n,p)$ with pmf $P(X=x) = {{n}\choose{x}} p^x (1-p)^{n-x}$. The general exponential form of an exponential family distribution is $p(x|\theta) = f(x) g(\theta) e^{\phi(\theta)^T T(...
1
vote
1answer
34 views

Interpretation of intercept only random effects models

I am estimating the global risk of infection risk in a population of patients, but these patients are clustered in hospitals and wards/departments. If I just take the crude prevalence (infected ...
1
vote
0answers
6 views

Coding a BEKK mutlivaraite GARCH model

I have the code, but I am struggling to determine which specific BEKK model it is for... Any advice would be appreciated, ...
2
votes
1answer
22 views

propensity score matching by disease and cox PH regression.. am I right?

Normally I understood propensity score matching is the way to match the treated group and untreated group. But I noticed some studies that used propensity score matching to match disease and non-...
1
vote
0answers
7 views

Hierarchical time series using DLM

I am developing a forecasting solution using R's dlm package and it is proving to be very useful for most of our requirements. However, I am also keen on sharing information among different time ...
1
vote
1answer
15 views

Regression model using combination of ranges/parts

My main goal is making predictions using a nonlinear model that have many independent variables. I would like to split my numerical independent variables into ranges/parts. Then to use a combination ...
1
vote
0answers
12 views

How to detect possible fraudulent administration of a survey questionnaire?

I'm involved in a survey on a highly sensitive topic, where I have reason to believe that the subcontractor who was responsible for data collection (a call centre) may have been pressured / paid / ...
1
vote
0answers
16 views

Fitting a neural network with more parameters than observations

I'm training a neural network for regression using keras with about 13k training observations, each with 40 features. It's a Sequential model with Dense layers. I generate random architectures for ...
1
vote
1answer
35 views

Leave one out cross validation with classification - is that possible?

Doing "leave one out cross validation" with a regression task is easy. You can calculate the MSE (mean squared error) even on one single sample and average them. But what about a classification task? ...
0
votes
0answers
12 views

How to implement a SARIMA-GARCH model

I was reading this paper about electricity demand forecasting and I'm interested in reproducing the model they claim to use : SARIMA-GARCH and the Reg-SARIMA-GARCH. There is no code linked to the ...
3
votes
2answers
25 views

Interpreting a Tukey - Kramer Confidence Interval Plot

In order to see if any statistically significant differences in the means of 4 particular diets exist, a post-hoc test is conducted i.e. Tukey – Kramer. Could someone please explain to me the plot ...
2
votes
0answers
44 views

Outliers on discrete data

Is there any robust methodology to identify outliers in the discrete data distribution. I am specifically concerned with discrete geometrical distribution? P.S. Data transformation does not seem to ...
1
vote
0answers
10 views

characterization of risk factors for a very rare condition

I am looking at a cohort of patients including 13000 patients, out of which only 160 have condition A. Out of these patients, only 6 have condition B. I would like to be able to characterize those ...
1
vote
0answers
7 views

d prime correction to use with a low number of trials

I am doing a psycholinguistic experiment, where I want to calculate d’ for each participant’s test scores. In the test, participants listen to 4 familiar words and 8 novel distractor words, and have ...
1
vote
0answers
6 views

mlbench synthetic datasets for python

Is there any implementation of the synthetic datasets from mlbench in python? I am looking for these implementations in particular. I've found sklearn.datasets for synthetic examples, but they do not ...
1
vote
0answers
13 views

Variance of unbiased estimator for the shape parameter of Pareto distribution

I'm interested in getting the error bounds of the unbiased estimator of the shape parameter ($\alpha$) using maximum likelihood method of Pareto distribution. The unbiased estimator is known to be $...
2
votes
0answers
21 views

Calculate incidence rate per person or in total

For my study I am doubting about the following: First I want to present the incidence rate for patients who received an CT-scan. I thought I would just count all the CT-scans that took place and ...
2
votes
0answers
22 views

Do mismatches in areas of peak density affect the KS-test more than mismatches in low-density areas?

In the following plot you see my empirical data (black) plotted against a hypothesised distribution (blue). However, a KS-test shows that there is no indication that my sample follows this ...
1
vote
0answers
6 views

KL divergence between sample and true (multivariate normal) distribution

I was wondering, whether there is a possible interpretation of the KL-Divergence between sample and true distribution in terms of probabilities. E.g. given $P=\mathcal{N}\left(\mu,\Sigma\right)$ and $...
0
votes
0answers
14 views

Multi-target Regression Neural Network: Trade Off

Suppose you have a number of input features, for example: x1 - temperature x2 - day of the week x3 - quantity of rainfall ... You are trying to predict a number of output targets - using neural ...
1
vote
0answers
22 views

Calculate number of points with expected values

The Problem Lets say you have a game where using an item gives you a certain number of points, with different probabilities for each point value. The probabilities are unknown, but can be estimated ...
0
votes
0answers
9 views

Understanding the MC dropout (Monte Carlo estimate)

I've recently came across the term "MC dropout" in one of the papers I was reading. In Neural Networks, when using a standard dropout layer on top of one of the model's layers, during training the ...
1
vote
1answer
11 views

Marketing Promotion modelling, effects of a competitor's promotions

I am modelling the impact of a manufacturer's promotions onto it's sales using a regression model. Furthermore, I intend to include the effects of competitor A's promotions onto the manufacturer's ...
1
vote
1answer
19 views

Power analysis for t-test instead of ANOVA

Let's say I have an experiment with a 2x2 repeated-measures design. Let's call the four cells A1B1, A1B2, A2B1, A2B2, for the factors A and B, each with two conditions, labeled 1 and 2. I want to ...
0
votes
0answers
5 views

Confused: The data length of covariations in a nonstationary GEV

I have established a non-stationary GEV model and expressed the location parameter μ(x) as a function of two covariates (x1, x2) to reflect changing conditions, while the scale and shape parameters ...
0
votes
0answers
6 views

Marketing Funnel Percentage Calculations

I implement a marketing funnel in python and I have an issue around the topic that I can't solve neither in statistical level. Lets say that we have the funnel A which contains ...
0
votes
0answers
6 views

Feeding Embedding Vectors With Time Series Data to LSTM [on hold]

I have daily sale data of some retail products on a three year span and I want to build a model that can predict future sales for all of these products. While looking for a way to forecast multiple ...
0
votes
0answers
11 views

R: Ordering data in a cell of data frame [on hold]

I have huge data frame of multiple columns, one of the column contain data like that ...
3
votes
0answers
40 views

Would an “importance Gibbs” sampling method work?

I suspect this is a fairly unusual and exploratory question, so please bear with me. I am wondering if one could apply the idea of importance sampling to Gibbs sampling. Here's what I mean: in Gibbs ...
1
vote
1answer
20 views

Word Embedding for Sentiment Analysis

I am working on sentiment analysis of text. I am using keras word embedding. If my embedding has a vocabulary of 50 and an input length of 4 and I choose an embedding space of 8 dimensions, how will ...
3
votes
1answer
43 views

Gaussian-to-gaussian transformations

It is well-known that when a linear transformation is applied to a normally-distributed random variable, the result is itself a normally-distributed random variable. I am interested in the converse ...
0
votes
0answers
5 views

What is the best calculation method to account for individual change, volatility, observation windows and time decays in time series data? ARIMA, ETS?

I am looking at applying a theoretical best calculation method to some particular time series (ts) data. Ideally the calculation method would encompass relative change in individual ts, volatility of ...

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