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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 ...

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Expected value of weighted random variable

I have a statistic I'm investigating that depends on estimates from a correlation matrix. The statistic is: $$ T = \sum_{i=1}^{m} d_{i} w_{i} $$ where $d_{i}\sim Bern(\pi)$ and is independent of $w_{i}...
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Question on a particular step in the Paule-Mandel 'Consensus Values and Weighting Factors' paper

I am preparing to use the Paule-Mandel method for determining the weighting factors in a meta-analysis. The paper I'm reading is the original one available here. I believe only those who are ...
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Magnitude of Weights vs Features for Output Layer

I have a question regarding the magnitude of weights and features for the output layer of an RNN. The RNN outputs a hidden layer matrix h of dimensions (64, M, N) which is then reshaped into a (64, M*...
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Given unnormalized weights in logs, how do I compute normalized weights in logs?

Setting Given a set of positive weights $\{w_i\}_{i=1}^n$, I can normalize them by computing $$W_i = \frac{w_i}{\sum_{j=1}^nw_j}\quad \forall i=1,...,n.$$ Easy enough. But for numerical reasons, it ...
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26 views

Quota sampling in R

I was provided surveys with quotas set at the provincial, gender, and employment status levels. I was wondering if it is possible to use survey package in ...
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Weight of MLP is larger than 1

I noticed when training MLP that weights of neurons can be larger than 1. Would this have negative effects on the outcome of the network? If yes, how to mitigate this problem?
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7 views

weighting survey data

I have an event that occurs in two location. Location Sample Event Texas 26211 122 Florida 23660 94 How do I weight the events based on the ...
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27 views

Combination of hierarchial time series forecasts with different methods - setting weights

I am trying to forecast the the number of orders for different products of a product group. I have the time series for each product. One of the problems is that some/most time series are intermittent ...
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When and how to use withSampW in the function get.weights of the Package twang?

I am using Twang R package in my analysis but I have doubt as to when and how should I use or not use the function get.weights. The package documentation here and ...
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37 views

Why does this simple weighted quantile differ from Hmisc::wtd.quantile? Which method is to be preferred?

It just struck me today that we should be able to use the weights method of stats::density.default to roll our own simple ...
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1answer
39 views

back propagation in neurons with zero weight and some specific conditions

I have read a lot of articles to understand what is happening behind the scene in backpropagation like Ive gone through this and many other like that. I think I understand how the backpropagation ...
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Effective sample size of a weighted sample

I am trying to understand the meaning of the effective sample size when we have weights for the sample. I have an intuitive understanding of why effective sample size can be less than the raw sample ...
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66 views

Is ratio of ranks a well-studied statistic?

I have two lists of recommendations: that is, two different algorithms have assigned ranks to the same list of objects. I would like to know if they're similar. I specifically care more about ...
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How to test for difference in weighted proportion difference? (and average weighted proportion differences)

Suppose I have a survey where respondents rate different questions as positive (1), negative (-1), or neutral (0), and their responses are given a different weight based on which job they have and ...
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Benefit of scaling survey design weights

In the european social survey the design weights are scaled to the sample size (see quote and source): As with the design weights also the post-stratification weights are scaled to the sample size, ...
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Assigning weights for binary endpoint analysis, using survival analysis

This problem concerns the evaluation of predictors which could potentially be used to decide on which patients to perform colonoscopy. Study design: Analysis of administrative data - patients ...
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31 views

Using multinomial logistic regression to make predictions [closed]

I have run a multinomial logistic model in SAS with 5 independant variables and I need to use the results from this model to make forecasts of use of care. I have used the predicted probabilities from ...
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11 views

Weighting data with uneven groups

I've seen that you can account for uneven amounts of respondents within different groups, but every example has the same amount starting. How do you handle if you have an uneven starting number per ...
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Shouldn't we consider larger standard errors for effect measures or outcomes that are converted in meta-analysis?

There are methods to convert effect measures in meta-analysis (pdf). There are also methods to convert outcomes; at least, I am aware of the conversion described in Furukawa et al. (2005) from ...
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images in the paper “Loss Surfaces, Mode Connectivity, and Fast Ensembling of DNNs”

I have some confusion about this image in the paper "Loss Surfaces, Mode Connectivity, and Fast Ensembling of DNNs" I am wondering what kind of technique they use to lower the dimension of the ...
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58 views

Simulating by hand the predictions of a complex mixed model with beta distribution from glmmTMB for diagnostic

I am conducting a GLMM for a meta-analysis using the beta distribution with the package glmmTMB. My response variable is a vector of correlations (No exact 0 or 1), but Fisher’s transformation fails ...
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2answers
193 views

Regression as a way to determine variable importance

At my work, we employ a nearest neighbor algorithm to classify records. Part of this process, of course, includes determining which features to use as auxiliary information in the algorithm. Also, ...
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1answer
52 views

Mixing of liquids where concentration follows normal distribution

We have several liquids where the concentration of a certain element follows a normal distribution, and we take a weighted combination of the elements. The concentrations are: $$C_i \sim \text{IID N}...
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How do sample weights work in classification models?

What does it mean to provide weights to each sample in a classification algorithm? How does a classification algorithm (eg. Logistic regression, SVM) use weights to give more emphasis to certain ...
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1answer
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Potential bias of effect sizes due to ceiling (or floor) effects when weighting effect sizes by their variance for meta-analysis

Regarding meta-analysis, I am wondering whether there is a potential bias due to the ceiling effects (or floor effects) when weighting effect sizes by their sampling error variances. In case of ...
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2answers
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How to find the weight of the weighted least squares regression analysis?

As the title, I am having trouble to the find weight at the weighted least squares estimation. I found that some people use weights like wts <- 1/fitted(lm(abs(residuals(regmodel.1)) ~ x))^2 or ...
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Weights of ratio of weighted data

Suppose I have the two datasets $x_i$ and $y_i$ with weights $w_{x,i}$ and $w_{y,i}$, respectively ($1 \le i \le N$). The weighted means are for example: $$\bar x = \frac{\sum_i x_i w_{x,i}}{\sum_i ...
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Which weighting to use for regression analyses at different levels of aggregation

I run a study with subjects in 400 groups of heterogeneous sizes ranging from 2 to 20 individuals. I have outcome data at the group level and at the individual level. Treatment was randomly assigned ...
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2answers
61 views

Reweighting features in PAM/K-means clustering

As stated in Hennig et al. 2016 Handbook of cluster analysis: If for subject matter reasons some variables are more important than others regardless of the within-variable variation, one could ...
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Formulating the Netwon Raphson

If this is the dataset under consideration and ...
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64 views

Regression with varying weights within fixed effect units

I'm running a regression where within the fixed effect groups, the weights are not constant. However, since there are many fixed effects, I would like to use an estimation method as implemented for ...
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63 views

Adding weights to forest plot with subgroups

I am creating a forest plot with subgroups (roughly following this example). Now I want each subgroups to be weighted as if I would plot them individually in a separate forest plot, and the weights ...
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33 views

Interpreting weighted MLE, MoM estimates with stochastic weights

I deal with the weighted probability density $h(x)=w*f(x, \theta)$, where x is the stochastic variable, f is the unweighted probability density, w is stochastic weight depending on x and also measured ...
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94 views

lmer in R: How and when apply weights to factor with 3 levels and unbalanced case numbers?

I want to run a mixed effects regression with lmer (package lme4) in R, predicting reaction ...
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338 views

Are frequency weights and sampling weights, in practice, the same thing?

Frequency weights indicate how many cases in the population a given observation represents. Sampling weights indicate the probability (sometimes the inverse of the probability) of an observation ...
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61 views

Weights vs offsets in logistic tree models

I'm interested in the differences in interpretation and functionality regarding weights and offsets in logistic regression trees. In my case, I am using XGBoost trees for logistic regression where the ...
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make weighted adjustment for sample selection bias

I have a survey results data which is know as biased. Each row record the age, education and ethnicity. I also I have census summary for the national population. So I know the basic results of ...
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1answer
32 views

How to compute adjustment weights to match marginal sums of a matrix?

I have a feeling this should be very simple, but I somehow got stuck thinking about it. I have $\it X$, which is a 15 x 18 matrix containing non-negative real values. I smoothed this matrix using a ...
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1answer
37 views

Can I use combination of eigenvectors as a single vector to explain most of variance?

I have a problem trying to find a combination (or weighted average) of variables (statistics) that best explains the sample statistics. A – n x p matrix (n: observations p: variables, here are ...
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68 views

Inverse weighted average

Is there something like an "inverse weighted average"? In my case, I have daily prices and daily units sold of a bunch of products and I would like to give prices with more units higher weights than ...
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1answer
47 views

Standard deviation of a ratio and calculation of weight

I have several "skilled" and "unskilled" wage observations for a number of countries, and would like to construct a single skilled-unskilled wage premium by country as the ratio of the simple average ...
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Can I compare coefficient values from different models?

I'm modeling conversions with a logistic regression. Each conversion can have up to 3 events (page visit, fill questionnaire, and call). I have 3 domains let's call them A,B, and C. Rather than using ...
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Final model equation for logistic regression with weights

I have built a logistic regression model with weights using glm function in R, as the event was rare. I used all 1's and 10% of 0's, then assigned a weight of 10 to each of the 0- rows and no weight (...
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What weight and how to use it for a 3 country analysis using the EWCS in Stata?

I'm fairly new to weights because the databases I used previously were not samples but actual populations I wanted to study, so apologies if all of this sounds very noobish. The way I understand it, ...
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158 views

Diagnostic residuals for Beta GLMM weighted by sample size (Meta-analysis) using glmmTMB

I am conducting a GLMM for a meta-analysis using the beta distribution with the package glmmTMB. My response variable is a vector of correlations (No exact 0 or 1), but Fisher’s transformation fails ...
0
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1answer
46 views

How to interpret the sampling weight of each observation in the dataset? [closed]

I have a data set containing a sampling weight for each observation. Here are the top observations from the data set : My question is what does this sampling (survey) weight means? How to interpret ...
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Can analytic weights be converted into sampling weights?

I am running a linear probability model, so I know I need to correct for heteroskedasticity. Since I know the variance of the error (from theory) to be $y(\pmb x)(1-y(\pmb x))$ where $y$ is the ...
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138 views

Weight minority classes using XGBoost (Multiclass)

I'm dealing with a multiclass problem in R using XGBoost. The dataset has 3 Classes representing the following proportion: 20% - 75% - 5%. Given the description above, it would be awesome some tips ...
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1answer
392 views

How to change a weight/bias with gradient

After watching 3Blue1Brown's tutorial series, and an array of others, I'm attempting to make my own neural network from scratch. So far, I'm able to calculate the gradient for each of the weights and ...
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Find a cost-sensitive multiclass algorithm

I am working on decision trees which can directly work in a multiclass context. My aim is reduce the misclassification's errors of a decision tree by improving its ability to tackle imbalanced ...