Questions tagged [references]

Questions seeking external references (books, papers, etc.) about a particular subject. Always use a more specific tag in addition.

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17 views

What is the mathematical description of “training” in supervised learning?

What are we trying to achieve mathematically when we "train" a model in the context of supervised learning? I have never seen a mathematical description of training in the context of ...
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1answer
113 views

Problems, which are difficult for SGD

I am doing some research on problems, for which the stochastic gradient descent doesn't perform well. Often SGD is mentioned as the best method for the training of neural networks. However, I've also ...
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1answer
14 views

How can i cite Sequential Forward Feature Selection (SFFS)?

I've seen many papers/books about this technique but none cite its author. Is it ok to cite any machine learning theory book that explains it? Thanks.
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1answer
18 views

Recommended books on Mediation Analysis?

I am interested in self learning Mediation Analysis. I have an MSc in Statistics, and I was wondering what would be an appropriate textbook to dig into this area. I would like something that combines ...
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10 views

Analyze Fantasy Premier League using SAS [closed]

Is there any recommendations to analyze Fantasy Premier League using SAS? (or any other Fantasy League - mostly just looking for an interesting way to practice SAS) I see lots of resources available ...
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0answers
23 views

Any introductory paper, dealing with 'logistic regression on time series data'

Question Can you introduce me any academic paper dealing with "logistic regression on time series data"? The difficulty of the academic papers that I want is the introductory level for ...
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6 views

PLS regression - VIP treshold to exclude variables

I have been developing PLS models in the software SIMCA. To optimize the model and decide which variables to exclude, I use the VIP (Variable Importance in Projection [1,2]) and in the software ...
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0answers
19 views

What is “conditional” about conditional GAN?

I was recently reading the conditional GAN paper https://arxiv.org/pdf/1411.1784.pdf In the conditional GAN paper, the author try to approximate two functions $D(x|y)$ and $G(z|y)$, where $x$ ...
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18 views

Seeking authoritative references on weighted ANOVA

I would be grateful for any reference, such as a textbook or peer-reviewed journal article (of any vintage), that contains explicit formulas for conducting a weighted ANOVA with arbitrary weights. ...
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1answer
26 views

reference source for multivariate gaussian processes

I'm studying Gaussian processes and currently reading the standard reference Gaussian Processes for Machine Learning. However, so far I didn't see any example of a multivariate Gaussian process nor ...
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0answers
48 views

A reference request for a population statistic---experienced population density?

We all know that countries (for example) have population densities, but suppose we want to know what is the actual experienced population density (that is, if, say, in Sweden 95% of the population ...
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0answers
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(Panel or time series) cointegration including one lagged variable

I have conviction that one of the variables in my vector can affect the rest only if it is lagged. For example, lets imagine a agriculture product which is planted in April of the previous year and ...
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1answer
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Mid-range via minimax

Warning: crossposted at Mathematics SE. Given vector ${\rm a} \in \Bbb R^n$, $$\begin{array}{ll} \displaystyle\arg\min_{x \in {\Bbb R}} & \left\| x {\Bbb 1}_n - {\rm a} \right\|_2^2\end{array} = \...
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Interpretation of Frobenius norm of covariance matrix?

Is there a statistical interpretation of the Frobenius norm of covariance matrix? More specifically, I have a transformation $Y=T(X)$ where the following holds, what can we say about $T$? $$\|E[YY']\|...
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How to extract and plot density alignment of GAN training?

In the source paper for GAN (generative adversarial networks), the generator (blue line) challenges the discriminator (green line) to achieve the true population density in black. Moving from the left ...
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1answer
25 views

How well does GAN (generative adversarial network) perform for small samples?

GAN is an unsupervised learning algorithm that pits a discriminator and generator against one another so that they iteratively compete to enhance the overall model's ability to model/replicate a given ...
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1answer
45 views

Book recommendation reqd - A book that teaches both, fundamentals of statistics and the related mathematical concepts, in a comprehensively [duplicate]

I am trying to build a foundation for data science through self study. Is there a book that could teach me the fundamentals of statistics along with the related mathematical concepts in a ...
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65 views

Carré du champ operator is a quadratic variation

Let $X_t$ be a real valued Markov process (starting at $x$) with generator $L$. Let $\Gamma(f)$ denote Carré du champ operator i.e. $L(f^2) - 2f \cdot L (f)$. As far as I know under suitable ...
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2answers
35 views

Book recommendations needed - building foundational knowledge for ISL - Introduction to Statistical Learning (by Gareth James)

I'm trying to build a data science base from scratch. I started a book called Introduction to Statistical Learning by Gareth James and found that there are many mathematical & statistical concepts ...
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2answers
29 views

Is it possible to classify images by vectorizing them (and achieve a good performance)?

Many applications of image classification involves convolutional neural network, where the image is treated directly as a 2D (or 3D, if multiple images) matrix. I wonder if images can be classified (...
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What are the underlying assumptions of MA, AR & ARMA processes, formally & informally and how do we test them?

I am new to the community and have recently started exploring time series analysis. I have seen a lot of answers here speak about how one tends to not focus on underlying assumptions and rather ...
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1answer
85 views

Quantitative methods book in R

I'm studying this book: Statistics: Unlocking the Power of Data to introduce me the basic statistics (quantitative methods). Throughout the book they use the software Statkey to do the simulations (...
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Linear mixed models: reference about effect sizes debate

I have heard many times over that there is "ample debate" about whether or not effect sizes (and also p-values) for linear mixed models should be computed and how they should be computed. Is ...
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1answer
46 views

estimation of distance between means of multivariate gaussian model

Assume that we have a large sample $X_{1}, \dots, X_{n} \in \mathbb{R}^{k}$ from a multivariate normal distribution $\mathcal{N}(\boldsymbol{\mu}, \bf{I})$. I aim to estimate the smallest distance ...
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1answer
55 views

Where to find a citation for the n/(n+1) sample variance correction?

In my Master's thesis project I could not show my (normally-distributed) samples to have a common population variance (through Levene's test or otherwise), so I could not use the n/(n-1) Bessel's ...
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Books for some kind of special self-education in probability and statistics theory?

I am looking for a textbook (or, more likely, a set of textbooks) in English for self-education in probability and mathematical statistics. I’m a middle-aged person working as data scientist, ...
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1answer
46 views

Theoretical justification of Parametric bootstrap?

I've been reading about bootstrap, and while it's relatively easy to find theoretical results (consistency and higher-order correctness) for the nonparametric bootstrap (e.g., Asymptotic Statistics by ...
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Literature of one-hot encoding performance v.s. others

For categorical classification, I couldn't find literature comparing one-hot encoding v.s. others from either theoretical or empirical point of view. I understand one-hot encoding is probably too ...
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0answers
16 views

Latest research and explanation on how semi-supervised learning is performing better than supervised?

So in AAAI 2020 also semi-supervised learning is given the push. There are some intuitive reasoning provided by people but since the research is so fast, I wanted to know actually what is the latest ...
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105 views

Is bootstrap problematic in small samples?

In "3 Things That Bother Me" (1988), Ed Leamer writes: Bootstrap estimates of standard errors are based on the assumption that the observed sample is the same as the true distribution, ...
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2answers
174 views

Nonparametric theory textbook(s)?

I am looking for a nonparametric statistical theory textbook that does not avoid tools from measure-theoretic probability and covers proofs on topics outside of rank-based hypothesis tests: e.g., ...
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0answers
14 views

Who first coined the term Ensemble Learning?

Who first introduced/invented the "Ensemble Techniques"? Is there any published research paper that first used that term?
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1answer
29 views

List of time series characteristics

Is there a source (paper, book, presentation, lecture) that gives an overview of all or most of the different attributes by which we can characterise time series signals along with definitions and ...
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1answer
31 views

Equivalence between ARIMA and HMM

The question is about the equivalence between ARIMA models and hidden Markov models in the context of time series analysis/prediction. Specifically: Can any ARIMA(p,d,q) model bet represented by an ...
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0answers
16 views

Statistical literature on task prioritisation problems

I am lookig for statistical papers on task prioritisation problems. In particular I am looking for solutions to the following problem or slight variations thereof: You have a set of tasks, each with a ...
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2answers
98 views

Seeking recommended literature search terms for a solution to a specific kind of data structure?

Hopefully this isn't considered too off-topic. I'm working in industry these days and came up with a solution to an analysis problem we'd been facing. I'd like to get a sense as to whether said ...
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1answer
29 views

Can entropy be used to minimize prediction surprises in machine learning?

Information theory deals with signal/noise identification, while one of its tools, entropy, measures the surprise in random probabilistic outcomes. Has there been any application of using entropy or ...
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1answer
35 views

Reference request: consistency of gradient boosting methods

I'm looking for work done on showing the consistency of gradient boosting methods such as gradient boosted decision trees. Friedman's original work only introduces the algorithm, but does not provide ...
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2answers
244 views

Looking for book recommendations for numerical optimization

I was reading the answers and comments to this question: Why is Newton's method not widely used in machine learning? and realised that I would like to learn a lot more about numerical optimization....
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0answers
28 views

Extremely basic question: how are data assumed to be generated in machine learning?

Given a dataset $\mathcal{D} = \{x_i\}, i = 1, \ldots, N, x_i \in \mathbb{R}$ In machine learning, what assumption is made as to how data are generated? I've seen two basic ideas circulating around, ...
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2answers
68 views

Statistics book recommendation for absolute beginners and non-mathematics people

Based on this this and this, but also looking for following specifications For absolute beginners level, and easy type book. Easy to read (Less text, larger fonts). Not mathematically rigorous. More ...
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3answers
241 views

Time series forecasting: from ARIMA to LSTM

I am looking for resources on the techniques for time series forecasting. It seems that there are three approaches, listed below in the order of their machine learning-ness (and correspondingly their ...
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0answers
19 views

Why and under what conditions does Q learning converge?

I am looking for a modern proof on why Q learning converges in the tabular setting. I've skimmed the original proof by Dayan and Watkins and I have to say that the terminology and approach are a bit ...
3
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1answer
39 views

Likelihood function when there is no common dominating measure?

When we have a statistical model $\{ P_\theta, \theta\in\Theta\}$ on some common probability space, usually we define "the" likelihood function $L(\theta)$ via a Radon-Nikodym derivative ...
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0answers
38 views

Classification with noisy labels, noise is structured and not random

I am building a classification model with mislabeled training data on the order of ~70% of the training data is labeled correctly and ~30% is labeled incorrectly. Knowing this, how can I quantify the ...
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11 views

Does “latent variable”, as in “latent variable model, latent embedding”, have a mathematical definition?

Does anyone know where this terminology "latent variable" first came into use and if it has a mathematical definition? I recently asked my professor in the context of VAEs and he said there ...
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135 views

How would econometricians answer the objections and recommendations raised by Chen and Pearl (2013)?

In their article, Chen and Pearl (2013), critically examined 6 econometric textbooks, among these the textbooks written by Wooldridge (2009) {the introductory book}, and Stock & Watson (2011). ...
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1answer
26 views

Interpret GARCH

is anyone know how to interpret GARCH model? I mean, maybe giving me some recommendations for books or research papers that contain an interpretation of GARCH in it? Thank You
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Power analysis for Ordinal Regression

I am looking for a resource to conduct power analysis for an ordinal regression that includes several predictors (there is no "treatment group"). I found a great simulation method first ...
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1answer
14 views

Website or app recommendation for Visualising statistics concept, comparable to VISNOS mathematics

There is a great website for visualising basic mathematics concepts, namely VISNOS. I am looking for similar interactive apps to visualise statistics basic concepts, especially how does the normal ...

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