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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 can I visualize weights of various Keras model layers?

Mostly just for funsies I want to visualize various layers of a Keras model as it's training. So, let's say I make a wee model: ...
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10 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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3 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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14 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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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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41 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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6 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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27 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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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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14 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 ...
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11 views

Deep learning model weights initialization problem in Tensorflow with given stddev

I am trying to create a model in tensorflow. However the weights initialization seems to be wrong but i cannot understand why. So, my model has a hidden layer with sigmoid as activation function and ...
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37 views

Standard error or confidence interval of a weighted average

I am calculating a weighted average according to, $f = \sum_{x=1}^{3} a_{x} \sum_{i=1}^{10} d_{x,i}w_{x,i}$, where $d_{i}$ are the values being weighted and $w_{i}$ are the weights. $a_{x}$ is ...
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1answer
39 views

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
20 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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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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23 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
38 views

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

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
190 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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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
47 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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76 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
36 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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2answers
60 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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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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29 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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12 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
17 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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91 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
92 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
6 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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68 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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37 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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6 views

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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39 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
41 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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1answer
52 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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0answers
18 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
25 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
55 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
78 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
90 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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39 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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1answer
69 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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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
315 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 ...