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.

Filter by
Sorted by
Tagged with
0
votes
0answers
4 views

Weights in Caret train

I would like to know more on the weights parameter in Caret train as I could not find any thing concrete from Caret documentation. Whether the weight indicates cost sensitive learning by engaging ...
0
votes
0answers
14 views

Unusual p-values after weighting

I'm still new to R and most probably this is a rookie question, but maybe some of you could help me understand what is happening. I'm analyzing some results of an experiment in which I have three ...
1
vote
0answers
27 views

Glorot initialization and gradient variance condition

In the Glorot initialization I don't understand why this condition should be validate to avoid vanishing/exploding gradient problem: "we need the gradients to have equal variance before and after ...
0
votes
0answers
13 views

Calculated standard error of two covariant variables of different weighting schemes

I have two variables $\bar{X}$ and $\bar{A}$ calculated as $\bar{X}=\sum_{i=0}^{n}w_{x,i}x_i$ where $x_i=i$ and $\bar{A}=\sum_{i=0}^{n}w_{a,i}a_i$ where $a_i=i$. From there $s_A$ and $s_X$ are then ...
0
votes
0answers
8 views

How do I properly weight an uneven (spacing) distribution of the numbers? [closed]

I have a set of numbers (depths actually) and I need to take the mean of another variable over these depths. For example, take the mean of temperature over a range of depths, however these depths are ...
2
votes
1answer
22 views

When performing matrix multiplications in neural networks, is it acceptable to do X * W rather than W * X?

I'm having a hard time seeing a clear convention being used and I've seen it both ways. X * W would assume the features (X) are in row format, and the weights are in column format. Is there anything ...
0
votes
0answers
3 views

Survey weighting for comparison of different groups

I have a survey with 4 questions (Yes/No) that I'm weighting using raking on age, gender, and country. I would like to subgroup to compare if young people < 40 to see if they have higher proportion ...
1
vote
1answer
27 views

Applying count models with rate responses

How do you apply count models to data which is count in nature, but a rate in reality? In such cases, r can handle this to a certain extent, depending on the model, but what is the correct way to ...
1
vote
1answer
47 views

How does the probability weight, called a pweight in Stata, work?

I am using inverse weights in a panel data analysis (fixed effects) in Stata, to see if my regression coefficients are the same after I reweight the analysis to better represent respondents most ...
0
votes
0answers
10 views

How to choose weights in neural network to fit implicaton?

I'm wondering what weights should be chosen in neural network to fit an implication i.e. $x_1 \Rightarrow x_2$ First important observation is that this logical statement takes value $1$ when $(x_1 =1, ...
0
votes
0answers
5 views

If I insert the exposure time as a regressor instead of as an offset in a Poisson regression, should I also weight for it?

I have, as outcome, the number of contacts with a medical service per week. Normally, in a Poisson regression, one should use an offset for the number of working days in the week. However, in my case, ...
0
votes
0answers
9 views

How to select the weights in a TOPSIS analysis?

In TOPSIS the sum of all weights needs to be 1 and that the selection of weights usually falls on the decision maker. At first it seemed to me that there was room for considering the weights as ...
0
votes
0answers
15 views

Weighted logistics regression when weights vary by random effect

I am investigating which factors (size, vocalizations, etc.) determine whether a nestling in a nest is fed each time a parent brings food to the nest. I have multiple nests (A-F), some of which have ...
1
vote
1answer
29 views

Why minimizing the ||w|| penalty term in SVM definition makes the overfitting less probable?

I understand overfitting and why we want our classifier to be reasonably simple. If we introduce more complexity to the predictor, we are risking that we fit it too closely to data, thus overfit, and ...
1
vote
1answer
45 views

How to efficiently calculate Skewness and Kurtosis of data having value with repetitions?

I am doing some research on stock data and somewhat new to advanced statistics. The data is for example Price --> Volume 100 ---> 1234 101 ---> 123456 102 ---> 6678 103 ---> 3456 104 ---...
0
votes
0answers
30 views

Difference-in-differences with inverse probability weights

How to design a model for DiD estimation where observations are weighted using inverse probability weights? I have a panel of villages and year. Treat=1 if village was treated (treatment time is ...
0
votes
0answers
14 views

How do I weight many-to-many relationships in a regression model?

In this context, I have 3 types of entities used to build a predictive model: subject - An individual. event - An activity performed by an individual at a particular time. target - An outcome that ...
1
vote
0answers
49 views

Sig Tests for weighted means

I got the challenge to integrate a test of significance into a Tableau dashboard. The dashboard shows weighted means for metrics such as income, age, etc. for two groups that can be defined by ...
2
votes
2answers
240 views

Weighting common performance metrics by classification outcomes?

Cost-sensitive classification metrics are somewhat common (whereby correctly predicted items are weighted to 0 and misclassified outcomes are weighted according to their specific cost). Some examples ...
0
votes
0answers
26 views

Variables' weights using PCA

I have recently read a paper where the authors applied PCA to determine the weights of the variables used to calculate a composite index. In the methodology, they mentioned that for a set of $N$ ...
2
votes
1answer
30 views

How to Increase the weight for one predictor variable?

Just read this news: "Zuckerberg agreed to increase the weight that Facebook’s algorithm gave to NEQ scores to make sure authoritative news appeared more prominently." My question is: how ...
1
vote
0answers
23 views

Are there time series models for weighted data?

Let's say I have the following time series: Weekly data spanning a few years; The dependent variable is the proportion of items that pass x. On average, that proportion is around 80%. The number of ...
2
votes
0answers
51 views

In general, how to determine the weight function of Robust regression

I think the question is clear from the title. How the weight function for example in Huber is calculated? Is it by differentiating the objective function?
0
votes
0answers
8 views

Include weight (or amount of noise) in each point into forecasting model

For each point I have information which is an inverse proportion to the noise per point. For example I would like to forecast the average purchase in shop per hour (as an example). Each hour there is ...
0
votes
0answers
44 views

Reduce skewness of normalized weights with outliers

I have a vector of values and I want to extract their weights so that they sum up to 1. I currently use this simple formula for normalization: $ w^i = \frac{ x^i }{ \sum {x} }$ The problem is that ...
2
votes
0answers
19 views

Pre-training without seeing data

Is there a solid reference on pre-training methods in deep neural networks which never see the actual inputs? Any such known thing in literature? I guess a more correct term is "initialization ...
0
votes
0answers
11 views

Raking weights - How can they possibly recover the joint distribution?

So I've recently encountered raking weights as a way to obtain weights for population level estimates: https://www.pewresearch.org/methods/2018/01/26/how-different-weighting-methods-work/. My question ...
0
votes
0answers
14 views

Weight of a pooled regression with panel data

I have a panel data set including both of the cross-sectional weight and longitudinal weight. And, I want to run a pooled regression. In this case, I think, it is right to use the cross-sectional ...
0
votes
0answers
5 views

reweighting one time series using proportions computed from another as weights in r

i have two groups of time series data about employment in two industries in two states. i need to figure out how to reweight one of the series for one of the states (for both industries) using ...
0
votes
0answers
12 views

Assigning weights to a list of averages when all I have is the mean, standard deviation, and number of samples

I have some data which, essentially, gives the change in value of a particular stock option according to 1 movement in price of the underlying stock value. For example, say stock 'ABC' has 4 different ...
1
vote
0answers
6 views

Impact of recoding variables on sampling weights

I'm working on a dataset with longitudinal survey data that includes final post-stratification weights. I want to recode some of the demographic variables, such as race and income, to combine several ...
0
votes
0answers
8 views

Forecasts combination via weights based on normal distribution

I am working on combining forecasts. I thought of calculating the weights based on normal distribution. This latter is fitted on the past values of the time series. My issue is, should the weight be ...
2
votes
0answers
110 views

Meaning of the weight argument in glmer and lmer

I have been looking into how to use the weight argument of glmer/lmer to represent "frequency" weights. I was ...
0
votes
0answers
55 views

Can IWeights Be Used as a Substitute for AWeights When Using XTPOISSON in Stata?

I am using a Poisson-regression fixed-effect model to estimate the effect that automatic voter registration had on the number of new Oregon voters in the 2016 general election. Since Stata does not ...
2
votes
1answer
53 views

Why doesn't the optimizer just look for stationary points of the loss function?

I want to have a better understanding of the weight-optimization process. I understand the optimizer(e.g., gradient descent) looks for the direction in which to move the parameters to minimize the ...
1
vote
0answers
49 views

K-Medoid Clustering with Point Weights

I implemented a K-Medoid clustering algorithm recently; I have a number of points $x_1, ..., x_n$ which have various properties and a distance function $d$ that maps two points to some nonnegative ...
1
vote
0answers
43 views

Increase one weight and redistribute other weights to add up to 1

I have a vector of weights that sum up to 1. For example: [0.1, 0.3, 0.4, 0.2] I want to force the first of these weights to be always at least equal to ...
0
votes
0answers
20 views

Are instance weights normalized in XGBoost?

I am useing XGBoost for a classification problem. I have a question concerning parameter min_child_weight. I want to make sure, hat a given minimum number of instances will be in every leaf of the ...
0
votes
0answers
21 views

Different outcomes between XGBoost and GBM observation weights

I've noticed that the weights argument in the xgboost and gbm r packages don't have the same effect. I had hoped to move from gbm to xgboost for performance reasons, but am not sure how to do so given ...
2
votes
0answers
92 views

Offset vs weigths in GLM

I was wondering from a technical perspective what approach I should follow in this modelling problem I have. I have a target variable Y which is a continuous random ...
0
votes
0answers
29 views

How to compute longitudinal weights for the two waves I have (in STATA)?

The first wave (w1) has 1000 participants and the second wave (w2) has 450 participants. Those 450 participants from w2 are recruited from the w1 (so they have definitely participated in w1). I now ...
0
votes
0answers
56 views

Can't replicate $R^2$ from a weighted regression in R

I need to calculate the $R^2$ for a specific regression model in R, since the specific function I'm using doesn't return it. I'm trying to do so based on this excellent answer, but am still unable to ...
0
votes
0answers
17 views

How to estimate weights for summation of variables

I have scores of two people, for which I want to create a combined score. This combined score is what I use as an independent variable. Currently I weigh both scores equally, so 50/50. But I have ...
1
vote
1answer
44 views

what's the purpose of trying to have small model weights via regularization?

In machine learning, it is often advised to use weight regularization so that the model parameters don't grow big while training. I am not convinced that having small weights improves the model's ...
1
vote
0answers
22 views

Assign more importance to recent records during training

I have a large dataset with information from the last year. I have to build a classification model in order to predict if a customer will buy a product or not (binary classification). Since in the ...
3
votes
0answers
14 views

Weights in multi-level models

I really hope that this is the right place to ask my question and that it hasn't been asked yet - otherwise please let me know. I am currently running a multi-level regression model with a cross-level ...
0
votes
0answers
47 views

Euclidean distance from zero

I am trying to create my own weights for relative work task importance, or weight. For every task, I have a value of importance, ...
1
vote
0answers
53 views

distance between two points (x,y) weighted by location (x)

a new on algebra. I am trying to create an indicator of the distance between two points (x,y) from a (0,1) scale, but I want to create a weight that reduces such distances as the point x is closer to ...
0
votes
0answers
30 views

Assigning weights to features for clustering

I want to run a K means clustering algorithm (using scipy/scikit) on a 1mn records dataset. I have a list of 5 features. Each of these features have a predetermined weight assigned to them: F1, 25% F2,...
6
votes
1answer
336 views

Non-normality in linear mixed models/GLMM

I have some data of time-depth profiles of whales. I want to model how the maximum depth of each dive (deepest point reached during a dive) changes between two dive types, foraging (if the whale feeds)...

1
2 3 4 5
7