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Bootstrapping regression coefficient for time series

One of the fundamental assumptions of bootstrap is that the samples are independent and identically distributed (i.i.d). This is the reason why it is difficult to bootstrap time-series because the ...
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1answer
4 views

Does High Information Value (IV) for a variable implies high coefficient in logistic regression?

I'm performing a Logistic regression for a binary classification task. As a preprocessing technique I use a transformation with WOE and Information value(IV), but I found something counterintuitive ...
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0answers
10 views

Does probability calibration always enhance the logloss?

I'm trying to calibrate some probabilities returned by different classifiers. I have plotted the auc and logloss of each one and ...
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0answers
3 views

Doubt on formulating cost function for GloVe

I'm reading the notes here and have a doubt on page 2 ("Least squares objective" section). The probability of a word $j$ occurring in the context of word $i$ is $$Q_{ij}=\frac{\exp(u_j^Tv_i)}{\sum_{w=...
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3 views

Variable and its dynamics in one multiple regression model

I am trying to find the dependence between default rates in bank and macroeconomic variables with linear regression. To do so I created a code which estimates every possible model - every combination ...
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0answers
9 views

LSTM cell state update equation wrong in Deep Learning book? (Equation 10.41)

In Equation 10.41 of the Deep Learning Book, the author writes the update equation of LSTM cell internal state as : $$ s_{i}^{(t)}=f_{i}^{(t)} s_{i}^{(t-1)}+g_{i}^{(t)} \sigma\left(b_{i}+\sum_{j} U_{...
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0answers
6 views

Difference between empirical and marginal reliability

I am using the mirt library in R to fit an instrument (binary responses) comprising two dimensions. In the mirt documentation are mentioned two types of reliability. I would like to ask what is the ...
-1
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0answers
9 views

what is the correct procedure to forecast future values of time series (how to fit the model to the entire series)

When forecasting future values of time series I have a hard time deciding which procedure to use. Your help is greatly appreciated. The problem at hand: there are several time series to be forecast. ...
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0answers
15 views

Should the standard deviation vary along the curve? [on hold]

I need to draw the error bars on a curve. in the images I have seen that this process is done, the bar lengths change from point to point. I am doing the calcualtions by Python. what Python asks me ...
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0answers
5 views

Multiple tests of variance

lets asumme I have one big dataset, for which I applied $m$ different models, leading to $m$ different out-of-sample (oos) results with $n$ examples/observations each. I now want prove that my ...
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9 views

Standardization and weights

I standardized my X variable with the non-weighted sample mean and sample standard deviation. I use sample weights in my analysis. Can I interpret my X effect as the effect of 1 non-weighted sample ...
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2answers
21 views

Is it possible to define an optimal fit?

Let assume that we have n pairs of real numbers: (x_1, y_1), (x_2, y_2), ..., (x_n, y_n) Let as also assume that ...
2
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1answer
14 views

Maximum Entropy Inverse Reinforcement Learning

I have been reading the paper Maximum Entropy Inverse Reinforcement Learning https://www.aaai.org/Papers/AAAI/2008/AAAI08-227.pdf and managed to get a good understanding of it through this lecture ...
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2answers
22 views

Should you take a sample when doing EDA?

Suppose i have a large dataset, such that python graphing libraries are unable to handle. Is it a good idea to take a random sample? Specifically if it's a classification task, and where the target is ...
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1answer
6 views

Principled way comparing and evaluating learned features/variables of estimators?

Does anyone know of any principled ways to compare and evaluate estimators based on what features have they learned. Basically I am interested in showing what features have these estimators picked up ...
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0answers
10 views

Log-Linear Models: Criteria for model selection for weighted data?

This is probably going to sound stupid, but I am a student, not someone who knows things, so: I am playing around with log-multiplicative layer effect models in R (and comparing them to less ...
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0answers
10 views

IRT warning message

I'm running a 3PL model with ltm package in R and I receive the following warning message: Warning message: In tpm(istdat, type = c("latent.trait"), IRT.param = TRUE) : Hessian matrix at ...
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0answers
20 views

Shouldn't there be a rung four on the the Ladder of Causation?

Referencing this question and its smart answer: I'm still confused and the confusion has been in part fueled by "recent" Pearl/Hernán tweets (tweet, tweet and tweet). Pearl's Ladder of causation ...
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1answer
16 views

Adding limits to regression coefficients

For my problem, I have data that contains daily observations of the total time and the volumes of task A completed, task B completed, C, D.. and I am looking to estimate the time it takes to solve ...
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0answers
7 views

Variable selection, variable reduction, and handling sparsity for binary text classification

I am trying to do a binary text classification using support vector machine. I am wondering if I am doing it right and I'd like to look for some answers to the questions in mind. The following ...
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0answers
5 views

Pre-hoc methods to determine sample size based on known number of features and classes

What are some pre-hoc methods that allow me to determine (or roughly estimate) sample size based on the known number of features and classes? I have found this article: Optimal number of features as ...
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0answers
11 views

How to Seasonally Adjust Data with Seasonal Dummies in R

I'm looking to seasonally adjust economic data and stock price data by using seasonal dummies/OLS in R. Could somebody please outline the steps to doing so from importing the data to ultimately ...
1
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0answers
17 views

Which has more mutual information with a multivariate Gaussian: its first principal component, or its first factor?

I have a $k$-dimensional Gaussian random variable $X\sim\mathcal{N}(0, \Sigma_X)$. What I want is a 1-dimensional scalar r.v. $Y\sim\mathcal{N}(0,1)$ that is jointly Gaussian with $X$ while maximizing ...
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0answers
12 views

How do I demonstrate standard deviation and error bars for multiple curves in Python?

I have 5 plots that are the measurements of a parameter from a test. So I need to find the average of these 5 plots to have one curve. and then determine the standard deviation. using Python, I was ...
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0answers
11 views

RNN vs Kalman filter

Being recently interested in Kalman filters and Recurrent neural networks, it appears to me that the two are closely related, yet I can't find relevant enough litterature : In a Kalman filter, the ...
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1answer
43 views

How many iterations are too many?

I have the following model: ...
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0answers
4 views

Obtaining VAE reconstruction probability

How does one calculate the reconstruction probability? Let's look at the keras example code from here. Is the reconstruction probability the output of a specific layer, or is it to be calculated ...
1
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0answers
8 views

differencing vs fixed effects

Suppose you have the model $y_{i,t} = \alpha+\beta_ix_{i,t}+\epsilon_i$ If you want to control for time-invariant omitted variables, you can either include fixed effects or use first-differences of ...
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0answers
5 views

How to interpret impulse-response functions in relation to beta and alpha coefficients?

How do I interpret impulse-response functions (IRFs) in relation to beta and alpha coefficients obtained from a Johansen cointegration test? For instance, my target (normalized) variable Y has a speed ...
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0answers
14 views

Interrupted-time-serie analysis/segmented regression - estimating the autocorrelation parameter

For my analysis of time series data in R I am following a tutorial paper describing the analysis step-by-step: Wagner, A. K., Soumerai, S. B., Zhang, F., & Ross‐Degnan, D. (2002). Segmented ...
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1answer
15 views

Can someone give a concrete example of exploitation in the context of Exploratory Data Analysis?

This post says Exploratory Data Analysis (EDA) consists of 2 steps exploration and exploitation. I know a little about exploration which uses some techniques such as data visualization to understand ...
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0answers
9 views

Deseasonalize data AND deflate with CPI?

I have property return variables and economic variables that I am using in a VECM/VAR to generate Impulse Response Functions. I have deflated my data with CPI, but do I also have to deseasonalize the ...
2
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0answers
18 views

Understanding PCA done on permuted data

Apologies if this has been asked before, nothing turned up when I tried to search. I'm noticing some very interesting behavior when I try to do PCA on pairs of some dummy datasets I just invented, ...
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0answers
9 views

Should we include “YEAR” column in time series data for any tree based algorithm? [duplicate]

I've a time series data having day, month, year and other columns. If I include year column during building random forest, then how can I predict for the new year. As the year passed won't be repeated ...
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0answers
9 views

How Many Residuals Should There Be for a One-Way rmANOVA?

As explained broadly across this site and in the stats literature, it is useful to check the assumption of normality in your ANOVA (analysis of variance) by plotting a QQ plot of the residuals of your ...
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1answer
17 views

Detecting change point in a time series

I'm dealing with time series from satellite imagery, where I have a sudden change (drop), that I can see from the plot, but I need a statistical test to detect it. I already checked for stationarity ...
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0answers
11 views

Time value errors when plotting high frequency time-series dataset using multiple Levels of Detail

Good morning, I have a series of measurements which are of 50 Hz signals, measured at 200kHz. The reason for the high sampling frequency is to detect any harmonics in the 50 Hz signals. I am ...
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0answers
6 views

Concomitant Variables in Finite mixture Models

On what basis does one decide whether a variable is to be taken as a concomitant variable in a finite mixture model (using flexmix in R)? With experimental data this seems easy to answer, but what ...
1
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1answer
32 views

How to use PCA to detect outliers?

A PCA will reduce the dimensionality of the original data and construct a subspace generated by eigenvectors of which each represents the (next) highest variance to explain the data. Let's start at ...
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0answers
8 views

Determining statistical confidence in conversion analysis

In this question the accepted answer states that we can think of each user who may or may not convert as a Bernoulli trial for the sake of simplicity. This makes sense, but the answer goes on to ...
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0answers
8 views

Multivariate regression with three groups in SPSS

I have three groups (Patient group 1 (N=32); Patient group 2 (N=41); Controls (N=74)). Age (continuous) and gender (dummy coded 0=male, 1=female) are my control variables. I have 1 predictor (...
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0answers
15 views

Outlier detection methods

I am analyzing some historical series to be used within the GARCH model. My idea would be to dteect any outliers in the series, so as not to introduce errors in the forecasted variance. Currently I ...
0
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0answers
31 views

Do we need parametric tests? [duplicate]

First of all, sorry for catchy title, my question is not that broad as it suggests. I just came to conclusion that I don't need parametric tests. Instead, I need some feedback if my reasoning makes ...
3
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2answers
44 views

Simple Linear Regression: $Y = \beta_0 + \beta_1 X$ BUT $y_i = \beta_0 + \beta_1 x_i + \epsilon$

I am studying simple linear regression for the very first time, and I'm having a little trouble understanding something. If someone can clarify this for me and perhaps lead the explanation to a little ...
0
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0answers
11 views

Which $n$ to use in the formula for standard error of a proportion

This question may be obvious to many but is not to me. I have found many variants on this question on CV but either they're not quite what I want or I don't understand them. I need to graph some ...
1
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0answers
11 views

Link between cross-validation and inference

Let's consider for instance Linear Regression and let's say we obtained some $t$-stats and confidence intervals for the coefficient estimates. Let's suppose we also split the datasets into $K$ Folds ...
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0answers
13 views

Gaussian Kernel and Feature Space

I have been reading this paper for a few days. There is one section (Section 3.3) that confuses me. We start by gathering local features from training images of a particular class into a single ...
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0answers
10 views

Extract only End of Month Prices Excel/R [on hold]

I have a dataset of daily closing sales prices and would like to filter the data to be left with only the last trading date of each month and its corresponding closing price, e.g. in the screenshot ...
2
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0answers
23 views

How to predict the standard deviation in linear regression?

When linear regression is formulated probabilistically using MLE, turns out that what we used to get as output, is actually the mean of $P(y|x)$, the latter is normal distributed around the correct ...
0
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1answer
17 views

Time Series Case Study

In time series, to forecast for 6 months, how much past data is sufficient ? I am having 13 years of data in file in which the first 3-4 years data is going down and then data is going up for the ...

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