Questions tagged [weights]

"Weights" may refer to: (1) observation weights that come from sample surveys -- consider tagging "survey-sampling"; (2) Monte Carlo sample weights that arise when sampling from intractable distributions -- consider tagging "weighted-sampling"; (3) variable weights in statistical or machine learning models such as regression, factor analysis, or learning networks -- consider tagging with that specific model. Other odd uses of weights go here.

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6 views

Weighting class estimator

What I understand is that in this scenario, the data is partitioned into Z weighting classes on the basis of variables observed for respondents and nonrespondents. $n_z$ represents the sample size, $...
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16 views

why choose this way of weighting [closed]

So i saw a piece of code calculating a score based on different variables with their own weights. I've usually only scores being calculating with weightings being applied to variables by; sum(...
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17 views

Multiply coefficients with different weights [closed]

I have two models with different weights (0.97, 0.11). Table of models and coefficients: Currently, I compute the final prediction using: $Prediction_{Final} = (Prediction_{Model1} * Weight_{Model1})...
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42 views

Complex survey design

I am currently analyzing a dataset resulting from a complex survey design. Individuals have been selected from a three-stage cluster sampling design with two strates (that have been combined to result ...
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52 views

Inverse probability of treatment weights and linear mixed effects models

I am encountering a problem when using inverse probability of treatment weights with linear mixed-effects models for a difference-in-differences analysis. I have longitudinal data on participants. I ...
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9 views

Help in learning feature weights

I need help with a problem. I have n features. With these features I can create a vector of size n. Given x vectors (where each vector is of size n) and a final score of the x vectors, what is the ...
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17 views

Perform k-means clustering after MCA for transforming categorical variables - provide weights to variables?

I have a very dataset with many observations (> 1 million), with mainly continuous variables and three categorical variables. After searching for clustering methods for mixed data, I decided to ...
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26 views

assessing the stability of importance (sampling) weights

I have read that when importance weights are used, the stability (variability) of the weights should be assessed (Levine and Casella, 2001) -- however, I wonder how this might be accomplished. For ...
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11 views

Is there a KNN method, that uses some sort of modell to predict weights for the used predictors?

Imagine a situation like this: You want to predict variable high (metric) by variable weight (metric) and ...
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1answer
10 views

Inferential considerations when comparing a group against the total

I want to compare the value of a subgroup against the same value in the total population in a regression setting. The easiest way to do it would be to treat the subgroup and the total dataset as two ...
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1answer
62 views

Why does gradient descent HAVE to find the minimum as oppose to a change in the opposite direction

I have a question about the gradient descent step in neural networks. I fully understand the derivative step and taking the steps required to move in the direction that reduces the loss (finding the ...
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1answer
23 views

Does the inclusion of a model offset convert predictor variables from counts to rates?

Does the inclusion of a model offset in Poisson or logistic regression convert predictor variables from counts to rates? Or does it only convert response variables from counts to rates? I understand ...
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1answer
38 views

Account for the number of Bernoulli trials in the response and selected predictors of GLM?

I have sampled animals at a number of sites and time points. Each site is sampled up to 4 times a year and is sampled over multiple years. At each site*time ...
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37 views

How to solve autocorrelation and convergence warning in GLMM (lme4)

I’m trying to use linear mixed model (random intercept and slope) to investigate if these factors have an effect on response variable (BL in the model) over years? ...
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1answer
29 views

fitting a betareg model with weights in R

I am using the betareg package in R to model a proportional response and would like to incorporate information about the level of confidence in each observation ...
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1answer
18 views

Variable Selection on a imbalanced data set

Suppose I want to perform variable selection on a highly imbalanced data set. Do I have to balance the data set either by downsampling the majority class or upsample the minority class before I ...
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17 views

Decision tree with weights trained using RandomizedSearchCV - do I have to refit?

I trained a decision tree with weights using RandomizedSearchCV: ...
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1answer
18 views

PCC as covariance of z-score scaled variables and weights incorporation

I've usually seen the Pearson Correlation Coefficient as : $$ \text{PCC}(u,v) = \frac{ \sum_{i \in I_u \cap I_v}{ (r_{ui} - \mu_u)(r_{vi} - \mu_v) } } { \sqrt{ \sum_{i \...
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5 views

Prevalence outcome with conditional trees

I'm creating a Conditional Tree model to predict the point prevalence of a certain event estimated in some health centers. I thought of using the proportional prevalence [0,1] as the outcome, but the ...
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23 views

Determining weights for fitting non-uniformly spaced measured data (v2)

Let's pretend I have some data to which I want to fit a line. If the data are uniformly spaced along the x-axis, I get the following: If the data are not uniformly spaced, I get a different fit line:...
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20 views

Determining weights for fitting non-uniformly spaced measured data

I have a system of generally known behavior, and some non-uniform measurements of that behavior (let's say without measurement error). Now I want to fit a simple function to a subset of the ...
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39 views

How does weights argument in gam() to handle the heterogeneous variance issues

In my case there were multiple observations per Group(random effect) in a single Year. So I aggregate these cases by calculating ...
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15 views

Selection of sample_weight for gradient boosted regression

I'm looking for any information on how the sample_weight parameter is typically selected for gradient boosted regression tree's - i.e. implementations such as ...
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14 views

Understanding how to weight variables

I am trying to model the "recruitment" of a deer population where recruitment is a factor of "females counted in fall" and "fawns counted in fall". e.g femaleFall:fawnsFall = Recruitment. In some ...
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6 views

Is Neighborhood Component Analysis weight correct for ranking inspection methods' ability to correctly categorise?

I am trying to figure out a good statistical method for establishing how effective different computer vision texture inspections are at correctly categorising images. I am basing my test off a paper ...
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18 views

Aggregate data for machine learning. Weights or fake disaggregation?

I have a dataset of medical centers and I need to predict their infection rate, based on the center characteristics and aggregated patient data (eg. percentage of patients which underwent a certain ...
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1answer
26 views

Proportional weighting of proportions

I apologize for the horrific title, but I can't accurately express what I want to ask. If I have eight observations with two groups with each observation having a ...
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1answer
50 views

Weighting data based on the errors

I have some data (counts) with a Poisson error associated with them and I want to fit the data. I am trying to weight the data inversely proportional to the errors, such that the data points with high ...
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1answer
54 views

Can Kruskal-Wallis test be used in groups of different size?

I am trying to compare Likert-scale answers to a survey applied in 3 different cities: A, B and C. I arbitrarily chose twice as many respondents from A, for a total of 500 answered questionnaires in ...
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26 views

Adapting weights for a glm() binomial regression [closed]

I've been facing a common problem. I can't use my dataset’s weights to estimate a binomial family model. I've been using the glm() function to estimate a probit model, but when my weights variable is ...
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64 views

Why does absolutely-summable weights ensures a linear series itself summable (convergent)? Some questions on def'n of Linear Series

A "linear series" $y_t$ is the linear combination $$y_t - \mu = \sum_{i=-\infty}^{\infty}\psi_iL^i\nu_t = \sum_{i=-\infty}^{\infty}\psi_i\nu_{t-i}=S(L)\nu_t $$ of weighted (by $\psi_i$ weights) lags ...
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52 views

Weighted Seemingly Unrelated Regression in R

I am using the systemfit package in R to estimate a system of three equations using the seemingly unrelated regression approahk ...
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39 views

How can analytical weights be used together with sampling weights?

I run a linear probability model (LPM) on survey data, which contains sampling weights. Say the predicted probabilities from the OLS regression are $\hat p_i$. Heteroskedasticity would make me ...
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17 views

In a regression to estimate propensity score, how can I build weights proportional to two different quantities?

I have a set of 88 people undergoing a treatment. My focus is on their contacts with a psychiatric service in the year before starting of the treatment, so I want an exact match wrt their previous ...
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9 views

Why does a non-decreasing weighting function ensure that rare word co-occurrences are not overweighted?

I was reading the original paper for the GloVe model and had a question. One page 4 of the paper under section 3: The GloVe Model, there is a portion that details properties that the authors' ...
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1answer
20 views

risk-ratio confidence-interval - but weighted?

I have survey data, with weights that adjust the sample to be nationally representative, from two time points. There is a binary presence/absence variable. Presence increases from time 1 to time 2. I ...
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8 views

Ranking with weights

I have a weak statistic background and I have tried to browse across similar questions but I still could not find the answer I am looking for. CONTEXT I work for a university with 20 academic ...
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41 views

How do I properly scale the covariance matrix in a weighted Gaussian mixture model for new samples?

I am trying to implement the method for computing a Gaussian mixture model from samples with known weights as detailed in section III of: EM Algorithms for Weighted-Data Clustering with Application ...
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1answer
286 views

How to understand the vertical bar (pipe) in R formulas [closed]

I came upon this because I wanted to emulate Welch's t-test using gls. I found the answer here: https://stats.stackexchange.com/a/144480/141304 and it says to add ...
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21 views

How LSTM compare which information is important or not?

I am interested to know, if I have scaled my data between [0,1], and have a vector like [0, 0.001, 0.01, 0.1, 1], is that mean ...
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8 views

How to interpret the transition and feature weights in a Conditional Random Field model?

Conditional Random Fields model have been a popular method for Named Entity Recognition as it accounts for statistical dependencies between entities and can include observed features that can aid with ...
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16 views

Weighting community-level observations in representative survey data

I am working with survey data that contain information at the individual, household and community level. The survey is representative at the national and first-administrative level but provides ...
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20 views

Appropriate weighting factor in weighted least squares regression

I'd like to construct a regression model with expenditure on a certain public service (a continuous variable in £s) as the predictor, and productivity (represented as a continuous variable on an index)...
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48 views

Model for taking a weighted average of a number of things, based on factors determining their significance

I am trying to model the following situation: There are a number of "events", each with a (real-valued) outcome. Ahead of each event, a varying number of parties can submit an estimate for the ...
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38 views

Is the weighted average of growth rates equal to the growth rate of a weighted average?

More formally, is the following statement true? Let $\alpha$ be between 0 and 1. \begin{equation} \alpha\frac{(A_t - A_{t-1})}{A_{t-1}}\ + (1-\alpha)\frac{(B_t - B_{t-1})}{B_{t-1}}= \frac{(\alpha ...
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84 views

Poisson mixed model with constant weights (glmer)

I have count data $Y_{i}$ associated with dates $d_{i}$ for $i\in\left\{1,\ldots,n\right\}$. I would like to model $Y_{i}$ in terms of a population "baseline" count and a date-specific effect. I am ...
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12 views

Weighting Survey data - Achieved sample, Survey sample, population

I have designed a small survey for my work place of 2000 people. 200 people were selected based on gender (Male female), age group (4 25-year age groups) and working grade (a,b,c). Out of my sample ...
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1answer
460 views

Weighted Categorical Variable

Consider for example I have a retrospective data that contains one categorical variable Race and one other variable Weight <...
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7 views

Observation-level weighted errors for classification models

I am building a classification model, on whether a particular outcome occurs or not. For each observation, there is an associated weight which is unique by observation, and should penalize ...
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21 views

Adjusting weights in meta-analyses using R

I am conducting a meta-analysis in R. Some of my studies provide more than one effect size for the same sample. I would like to account for this by adjusting the weight that each within-study effect ...