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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Replication, reproducibility and machine learning - reference request

Are there any papers where machine learning (NLP) was used to assess if papers would be reproducible? I remember something I think it was from a researcher in Harvard but I cant seem to find it.
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1answer
35 views

Reference request for Kendall's Tau

I need some reading suggestions on Kendall's Tau at undergraduate level . I am not able to find some good material on the above topic . Please help me out . EDIT: To be more specific ,I want some ...
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1answer
78 views

Gauss' proof that “the best estimate for a random variable is the average”

I have read that "Gauss proved that the best estimate for a random variable is the average." Can someone provide Gauss' publication containing that proof? To be clear, I am not looking for you to ...
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0answers
26 views

Model Selection and inference for mixture of logisitc regressions (or GLM) with heterogenous covariates by component

I am facing a problem which should be quite common IMO but for which I don't find relevant contribution. So the situation is this. Let's say that a binary response $Y$ is generated by a mixture of $K$ ...
2
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1answer
103 views

An inequality giving a sharper bound than that given by the Chebyshev's?

Let $X > 0$ be a random variable; let $P$ be the underlying probability measure; let $\delta > 0$. I wonder if there is already in probability literature a known result giving a sharper bound ...
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0answers
39 views

Time series data with mixed calendar and fiscal year

I am performing time series analysis with yearly frequently. However I need to regress a data compiled by calendar year against another compiled by fiscal year. Is it possible to deal with this? If ...
3
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0answers
49 views

Optimization textbooks for statistics and data analytics

Any statistical analysis, machine learning or data science involves some sort of optimization at the end of the day. I'm looking for good linear and nonlinear optimization textbooks for self ...
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0answers
31 views

ILSR + mathematical precision = perfect book

I very much like the famous "ILSR" book by Hastie, Tibshirani et al! Lots of nice R experiments and good intuitive background is explained - but what the book in my opinion lacks though, is ...
6
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1answer
450 views

Is there any paper which summarizes the mathematical foundation of deep learning? [closed]

Is there any paper which summarizes the mathematical foundation of deep learning? Now, I am studying about the mathematical background of deep learning. However, unfortunately I cannot know to what ...
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30 views

Real world stat practice

I've been taking courses in Applied Statistics and through the homework problems I get to practice what I've learned. But, I find that the practice problems are always a bit contrived to fit within ...
2
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1answer
132 views

Deriving a filter like a Kalman filter from a non-Gaussian state space model

Assume we specify a state space model as $$Y_t = a X_t + W_t$$ and $$X_{t+1} = b X_t + V_t$$ where $b,a \in R$, $E[W_t] = E[V_t] = 0 \quad \forall{t }$ and $W_t $ and $V_t$ are indipendent for ...
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1answer
657 views

What's the history of box plots, and how did the “box and whiskers” design evolve?

Many sources date the classic "box plot" design to John Tukey and his "schematic plot" of 1970. The design seems to have stayed relatively static since then, with Edward Tufte's cut-down version of ...
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1answer
79 views

POMDP books/lecture notes/tutorials

I'm looking for good references to learn more about POMDPs, preferably from a more mathematical stand point. The only good reference I've been able to find so far is: http://www.cs.toronto.edu/~...
2
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1answer
27 views

Is there any theory on the order of Autoregression model for periodic time series? [closed]

Say M periodic signals, then one can safely say using AR-M model can achieve the perfect prediction. But how about further, in a more general sense, is there any publications on this? Update: Here ...
2
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1answer
72 views

reading books about Bayesian Model selection

I was trying to find some "good" reading books about Bayesian Model selection. So is there any recommendations? To be specific, I was trying to understand the Bayesian Information Criterion (BIC), the ...
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2answers
63 views

Book reference request for statistical reliability theory

I'm about to learn statistical reliability theory for the first time. I'm told that Barlow and Proschan's book entitled "Statistical theory of reliability and life testing" is a classic on this topic. ...
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2answers
109 views

What is the most powerful result about the maximum of i.i.d. Gaussians? The most used in practice?

Given $X_1, \ldots, X_n, \ldots \sim \mathscr{N}(0,1)$ i.i.d., consider the random variables $$ Z_n := \max_{1 \le i \le n} X_i\,. $$ Question: What is the most "important" result about these ...
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2answers
403 views

Time series analysis textbooks for mathematicians

As a former mathematics student, when reading any math-related materials I tend to care about their mathematical rigour very much. Such high attention to mathematical details might be a good habitat ...
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0answers
32 views

Looking for visualizations in probability and statistics

Are there any online resources or books where probability and statistics concepts are explained in schematic pictures and plots? What I am looking for is: let's say while explaining marginal, a 2d ...
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0answers
30 views

Is there any Good comprehensive reference for tensor calculus? [duplicate]

I am currently reading this RNN blog, where it talks about Backprop through time. I am struggling to derive it and don't understand how to go about such derivations in general. Stuff like this ends ...
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1answer
47 views

Applied machine learning reference

I am looking for a reference on applied machine learning, esp. around model deployment to production environments and model evaluation. There are plenty of references about models, how to learn models,...
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0answers
43 views

Gaussian process with interval observations

The stochastic process $(X_t)_{t \in T}$ is a Gaussian process if the marginal distribution of $X_{t_1}, \ldots, X_{t_n}$ is a multivariate Gaussian distribution for all $t_1, \ldots, t_n \in T$. Let ...
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0answers
24 views

References for Texas Holdem

Does anybody know any good papers or software that use Monte Carlo techniques to estimate the probability of certain hands or winning/losing a hand in Texas Holdem? Ideally I'd like to have some ...
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0answers
28 views

Any book containing a collection of exponential smoothing papers from 1950s/1960s such as those by Holt?

I would like to read the originally published papers to see how the structure of the equations is justified. I would especially like to read Holt, Charles C. (1957). "Forecasting Trends and Seasonal ...
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0answers
19 views

What is the most consequential duality in Statistics? [closed]

I mean ‘duality’ in the strict mathematical sense, not merely as a synonym for ‘symmetry’.
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1answer
58 views

Reference for matrix-variate($n\times m$ random matrix) normal distribution

I'm looking for a document with some few pages with the basic properties of the Matrix-Variate Normal distribution, with an applied perspective. Is there such document? If not, what's the most similar ...
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0answers
66 views

Weak instrument problem, how can a “false experiment” serve as an identification check?

In their 2004 paper, Miguel et al. investigate the role of income growth by using current and lagged rainfall as an instrument. However, the instruments are somewhat weak: the joint F-statistic is ...
2
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1answer
175 views

What is $\lambda_{min}$ that makes all regression coefficients zero in LASSO regression [duplicate]

I learnt that in LASSO regression, there is this $\lambda_{min}$ which is given by $$\lambda_{min} = \text{max}_j|\sum_t y_t X_{tj}|$$ in which $y$ is the response, $X$ is the matirx of predictors. ...
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0answers
28 views

citations for studies that fit different machine learning models for different individuals? Or even within one individual?

Can anyone reference papers that fit best subset/lasso/ridge regression or other “machine learning” models (dimension reduction) for a SINGLE person? Say for example you had a child read several ...
3
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0answers
48 views

Overview articles on Bayesian philosophy and methodology

While we have questions about Bayesian textbooks (1 and several other) and the philosophy behind the Bayesian thinking (2), I am interested papers (or sources of similar length, e.g. blog posts or ...
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1answer
83 views

Prerequisites for Learning Regression [duplicate]

I am doing self-study to learn Data Science (software developer by profession) and needed to read and understand ISLR but this book requires Linear Regression as prerequisite. I searched here and got ...
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1answer
26 views

analysis of optimal neural nets?

Neural nets are trained with learning algorithms that are very very unlikely to find the global optimum in parameter space (i.e. the global optimum neural net out of the set of possible neural nets ...
3
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1answer
66 views

How do I learn when to apply which statistical distributions? [closed]

I am learning Bayesian modeling and having trouble keeping straight when it is most appropriate to apply the various statistical distributions beyond the basic ones like the beta, binomial, and ...
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3answers
4k views

What are the current state-of-the-art convolutional neural networks?

I'm interested in understanding which neural network architecture is currently the state of the art (sometimes abbreviated "SOTA") with respect to standard image classification tasks such as MNIST, ...
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1answer
719 views

Book Bayesian statistics [duplicate]

I write here to ask for a suggestion about a graduate level Bayesian statistics book. I have a bachelor degree in statistics but despite having a fairly solid background on frequentist and non ...
4
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1answer
63 views

Scientific source for why reporting p-values of random effects is not meaningful?

I have read a lot about why most statistical packages do not report the significance test results of random effects (e.g. here) Is there any publication about this precise topic that I could use to ...
3
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0answers
36 views

Texts on visualizing big data

I am looking for textbooks, papers or alternative material focusing on ideas and general principles for visualizing big data. By big data I primarily mean wide data, i.e. high-dimensional data, but I ...
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0answers
24 views

Extensions of logistic regression in the context of machine learning

I was wondering whether there exists an overview about all extensions of logistic regression in the context of a machine learning approach. E.g. instance-based logistic regression (Cheng and ...
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0answers
40 views

Testing for identical response

In a recent task at my job I have come with a situation I cannot find references to research made about it. Basically, I have two procedures and I want to test if they behave exactly the same way (i.e....
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0answers
204 views

How were statistical distributions discovered?

Let me start, that i know that it's not very difficult to generate a probability distribution. If one takes any positive integrable function and normalizes it, this results in a probability density. ...
3
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1answer
152 views

The Book of Why, Table 8.1, Counterfactuals example

I'm reading "The Book of Why" by Judea Pearl and I'm getting an answer for a problem that doesn't match what the book says. This is my first foray into Structural Causal Models and their use, so I ...
6
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1answer
836 views

Should I gloss over the linear algebra chapter in the book “Deep Learning” by Ian Goodfellow?

Currently I am reading "Deep Learning" by Ian Goodfellow, Yoshua Bengio, and Aaron Courville. I'm on Chapter 2 which is the Linear Algebra section where they go over the linear algebra that pertains ...
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0answers
48 views

Textbook covering multiple linear regression with stohastic regressors for time-series

I am looking for a textbook or some other resource where the following multiple linear regression problem is considered. The model is: $Y_n = \beta X_n + a+ \epsilon$ Where $\{X_n\}_{n\in\{0,...,T\}...
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1answer
75 views

A question about markov decision process

I was thinking about markov decision processes and asked myself if the following idea has been explored in the literature: Suppose that to each state we have a vector of variables and the reward and ...
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0answers
35 views

Good book on characteristic functions that includes the CF-proof of the CLT

The title basically says it all. I would like to learn about CF in order to understand the proof of the CLT that makes use of CF. Ideally I would like to read a book that does not only give proves of ...
4
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0answers
35 views

Computational statistics review

I'm looking for a mathematically rigorous review of key topics in computational statistics, such as numerical integration, EM algorithms, MCMC, and sampling algorithms. Are there any good lecture ...
1
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1answer
169 views

What are the regularity conditions for quasi-maximum likelihood estimators?

What are the regularity conditions for Quasi-Maximum Likelihood Estimators (QMLE)?1 Could you advise me a good book where I can find detailed proofs? 1. For example, regularity conditions for MLE ...
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1answer
42 views

Multiple Regression Quadratic Assignment Procedure

Can you advice a paper or a book about ''Multiple Regression Quadratic Assignment Procedure'? I need information about the essentials and the assumptions of the procedure. Thanks
3
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1answer
58 views

Generalized least squares error estimation

First of all, I have to admit that I am not statistician so some of my nomenclature could not be very rigorous and maybe a bit confusing; pleas ask me to clarify if necessary. The Problem Let's say ...
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1answer
432 views

Choosing the right stats textbook - graduate level

I want to do some self studying over the course of the summer. However, I find it hard to choose a good textbook amongst the plethora of possibilities. I study political science at graduate level. So ...