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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 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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How to rank observations with two variables (website performance)

I have no background in statistics, so I find myself confused by this simple problem. I'm not even sure which search terms to use. I have some website performance data. I have the number of times a ...
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1answer
14 views

downloadable weights of VGG-16 during ImageNet training

Does anybody know a place from where it is possible to download the weights of VGG-16 at different epochs, along a succesful training on ImageNet? The ideal situation would be to have downloadable ...
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11 views

Statistical methods for assigning weights based on rank differences?

I have encountered methodological problem in my pursuit of my master's degree, and I hope you can help! I know exactly what I want to do, but I do not know which statistical area this is related to. I ...
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9 views

Two-tails Kolmogorov-Smirnov statistic between the two weighted samples

I am trying to calculate a Two-tails Kolmogorov-Smirnov test statistic for two weighted samples. The only reference that I've found is in Numerical Methods of Statistics by Monohan, pg. 334 in 1E and ...
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1answer
26 views

How do I apply weights to a Cox Regression Model in R?

I am trying to answer the question of whether service in a certain organization has an effect on age of first marriage, and am interested in using the Cox model to understand the difference in the ...
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2answers
62 views

Why do we use Gaussian distributions in Variational Autoencoder?

I still don't understand why we force the distribution of the hidden representation of a Variational Autoencoder (VAE) to follow a multivariate normal distribution. Why this specific distribution and ...
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6 views

Prioritising Markets - deriving weights for paramters

I am in the process of developing a market prioritization model. I am using data predominantly from census information. I have created buckets of information such as lifestyle and household ...
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1answer
36 views

IPTW for multiple treatments

I am dealing with a dataset where patients are subjected to multiple treatments A or B or C or D . Since there are four treatment options I am using multinomial regression to estimate the propensity ...
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1answer
23 views

Reference request: initializing big neural networks with small neural networks

I am currently trying some meta-algorithms on training neural networks. Start with a small but expressive enough network for training and after several epochs, initialize a larger neural network with ...
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74 views

Weighted Wilcoxon rank sums

I want to test for differences in a non-normal continuous variable between group A and B. I want the test to account for the inverse probability density weight (IPW) of being in group A. My own idea ...
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1answer
25 views

How to analyze BRFSS survey data in R? How to set `id`? [closed]

I am trying to analyze BRFSS in R with weights for complex survey design using the survey package. I am confused as to what to set ...
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0answers
6 views

How to assign weights to repeated measurements data, where measurement accuracy decreases, when fitting a model with nlmer() - lme4?

I am currently working on a problem where I am required to fit a nonlinear mixed-mixed effects model on a repeated measures data using nlmer(). Here are the details of my problem: Data: I have data ...
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2answers
59 views

The correct formula for weighted average

The formula for a weighted average is: sum of values, multiplied by respective weights, divided by count of values. Right? That’s what I thought it was until I saw other variations, which are ...
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12 views

Kriging with Weighted Data

I have a point-level dataset of apartment building level rent. I have the average rent per square foot per building and the number of units in that building. I would like to krige a surface of points ...
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28 views

Is deletion a form of weighting?

If observations are weighted in a regression model, is there are requirement that $w>0$ when calculating weights? It should be noted that some forms of weighted univariate statistics are special ...
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11 views

How does missing data affect analyses using svyset?

I am running some simple statistics using Stata and its svyset command. Does listwise deletion of cases during analyses affect the svyset? Are results still going to be weighted properly and the ...
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1answer
16 views

Un-standardize feature weights

I have a linear regression model $y_a = \theta_a^T\tilde{f}$, where $\theta_a$ is a vector of learned feature weights and $\tilde{f}$ is my standardised feature vector; $$ \tilde{f} = \frac{f - \mu}{\...
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23 views

Balanced LogLoss with XGBoost

Following the discussion on here I started worrying less about class imbalance. However, I recently started building a predictor, using XGBoost, and I wanted to used LogLoss as my target metric. I ...
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1answer
79 views

How to solve an adaptive lasso model?

Assuming we are working with a linear regression model, lasso penalization solves: \begin{equation} \min_{\beta}\left\{\left\lVert y-X\beta\right\rVert_2^2+\lambda\sum_{j=1}^p \left\vert \beta_j\...
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4 views

Possibility of constrain the product of norm of weights across all layers

Problem One theoretical result I read says that the generalization error of deep neural networks could be independent of network depth and width when the product of norm of all weights across all ...
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0answers
7 views

Weighted D optimality

I am working with D optimality for nonlinear models. My model has 8 parameters and some are more important than others. Is there a way to give weights to each of the parameters? I am thinking of ...
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0answers
4 views

Events with two sets of weights - correlated weighted Poisson distributions?

Let's say I have a set of $N$ events with weights $w_i$. $w_i$ follow some distribution, the same for all $i$, that I either know or can approximate. $w_i$ and $w_j$ are uncorrelated for $i\ne j$. ...
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56 views

Stabilized propensity weights: intuition and ATT formula

The average treatment effect (ATE) of binary treatment T on outcome Y can be estimated using inverse propensity weights: \begin{equation}\nonumber \frac{\sum_{i=1}^{N}t_i\hat{\pi}_i^{-1}y_i}{\sum_{i=...
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0answers
32 views

Combining multiple observation weights for classification

Let's say you have multiple sources of observation weights for a dataset. For example, you have a $[0,1]$ weight coming from the label's certainty ($w_c$) and another one coming from its recency ($w_t$...
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Weighting cases if some population groups are missing in a sample

A usual way to weight cases in a sample for the $i$ category is taking its weight as $w_i$ = $P_i/p_i$, where $P_i$ is known proportion for that category in the population and $p_i$ – in the sample. ...
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1answer
18 views

Tensorflow choice of values of variables after training [closed]

I am trying to build a neural network, that is able to perform a linear regression. After for example 1000 epochs, I encountered the situation, where the smallest loss-value was not the last loss-...
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34 views

Effective Sample Size for Weighted Samples

I have an MCMC sampler with weighted samples and I want to compute effective sample size at every step to determine sample degeneracy. I am using the following formula: $ESS = \frac{(\sum_{i=1}^N{w_i}...
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1answer
38 views

Save Machine Learning Model progress for later [closed]

another dumb question, but how do you save the progress an ML model has made and start from that point later? Its kind of a vague question, but this is an example of what I am talking about: Say, ...
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29 views

Why does weighting increase the standard error of an estimate of a proportion?

Imagine I am running a survey with a non-probability sample. The population is 5,000 people, and my sample is about 100 people. There are two binary variables, $x_1$ and $x_2$, that predict the binary ...
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12 views

Wrong weights learned when training RBM

I'm training my RBM network and on epoch #4 I have such a filters representation (my weights matrix) But on the next iteration (fifth epoch) something went wrong and my filters became like this What ...
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1answer
24 views

How to compare multiple weight vectors of different size?

I am facing a statistical problem that I am not sure whether it's solvable. Simply put, I am given multiple weight vectors and here are two examples: $w_1 = [.2, .3, .4, .1]$ for items A, B, C, D, ...
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1answer
43 views

What are the theoretical/practical reasons to use normal distribution to initialize the weights in Neural Networks?

I'm aware that there are many different practices of initializing the weights when training a neural network. It seems traditionally standard normal distribution is the first choice. Most articles I ...
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1answer
71 views

for a multinomial treatment and binary outcome, what is more appropriate, ATC or ATE?

I need help to choose between ATC and ATE for my analysis with multinomial treatment and binary outcome. In the example below taken from here, it seems that ATT does not sound well for multinomial ...
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1answer
69 views

how to calculate manually propensity score weights for multinomial treatments where one of them is baseline

I want to get intuition into the calculation of propensity scores (PS) and inverse probability of treatment weights (IPTW) for a multinomial treatment using multinomial regression. One of the ...
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1answer
16 views

Is there a way to check the full learnt function by Neural Network, not only the weights? [closed]

The training is mostly learning about the wights.But what about the full function learnt by NN? In typical deep learning framework, is there a way to example the function learnt? For example: ...
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0answers
24 views

Weighted covariance with different reliability weights?

Suppose observables $X$ and $Y$ possess different reliability weights $w_{x,i}$ and $w_{y,i}$ for the possible elements $x_i\in X$ and $y_i\in Y$ respectively. Considering a sequence of consecutive ...
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25 views

Should weights be applied in generated quantities block in stan?

I want to do predictions via generated quantities block in stan. I have two questions: Should the weights be applied again in the generated quantities block in addition to the likelihood in the ...
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0answers
19 views

“Strongest held belief” tests - data analysis problem

The data comes from an online test where each question only has a yes/no answer. There's no pattern or theme, and each question has an equal random chance of being asked. There are hundreds of ...
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3answers
126 views

What are weights in a binary glm and how to calculate them?

I have a dataset that includes four variables. Three of them are factors and one is constant. My response variable contains (0,1) so my glm is about logistic regression. My question is, how do I know ...
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0answers
43 views

Weighted Empirical Cumulative Distribution Function (CFD): order values before or after weighting? [before]

My input data are some observations of a continuous variable, let's say the number of kilometers of motorbikes. I did a survey and I collected some observations. Somehow, I computed weights for all ...
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1answer
95 views

Why does weighted bootstrap have awful coverage even in toy example?

I'm interested in using the weighted bootstrap to correct for selection bias with a known form. I simulated a very simple example where the underlying data, $X$, are $N(0,1)$ and we are calculating a ...
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0answers
24 views

Sample weights in covariance matrix estimator

I am using Logistic Regression with count representation. So, for any feature-tuple, I have few 0's(negative class) and few 1's. I duplicate each row, one for target 0 and other for target 1, And I ...
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0answers
152 views

How to use data_utils.WeightedRandomSampler and still be able shuffle training data in Pytorch?

I am working on the multi-label classification task in Pytorch and I have imbalanced data in my model, therefore I use data_utils.WeightedRandomSampler method ...
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0answers
25 views

Regarding frequency and inverse probability weights

Deploying inverse probability weighting on a 3-group Setup, I examined for outlier activity, aswell deployed in a survey bin. Regression model. These estimates of ...
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0answers
30 views

Error variance estimation with weights

I am using data which include a (sample-)weight for each observation, i.e. the data is from a survey that has weights to make the sample representative for the US-population. I perform OLS to get some ...
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1answer
78 views

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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21 views

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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0answers
7 views

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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1answer
70 views

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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1answer
75 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 ...