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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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Some Recent Mathematically Rigorous Deep Learning Papers [on hold]

I am looking for some mathematically rigorous recent deep learning papers. Can someone suggest some?
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35 views

What are some introductions to classical statistics that emphasize unifying principles? [duplicate]

I'd like to know an introduction to classical statistics, that: Emphasizes connections and unifying principles (I checked this question and the links posted therein, but didn't find an introduction ...
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Variable Importance for Logistic regression with categorical data?

If I run the logistic regression with X variables containing categorical data. (I do one-hot encoding on categorical data) How do I evaluate the variable importance? Is there any methods or literature ...
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5 views

Fusion gene detection from TCGA or ICGC data

My PhD project involves fusion gene detection from cancer data of TCGA and ICGC portals. I find that the RNAseq files (fastq,bam formats) are mainly closed access, whereas the clinical or expression ...
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0answers
18 views

Clearing out errors from a data set

Sorry for the vagueness of the title, I am having a hard time even coming up with sort of problem I am facing (if there is a specific name for it....) In a nutshell, I have a time series of points, ...
4
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2answers
67 views

What are the best books to study Neural Networks from a purely mathematical perspective?

I am looking for a book that goes through the mathematical aspects of neural networks, from simple forward passage of multilayer perceptron in matrix form or differentiation of activation functions, ...
2
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2answers
58 views

In hypothesis testing why do we need to use the reject null hypothesis approach but not the other way round?

In hypothesis testing, the common approach is to first set a null hypothesis and a hypothesis we want to test. Then apply some statistical techniques and see whether the observation is likely to ...
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0answers
8 views

Offline signature verification - deep learning

I am looking for good articles to read about offline signature verification using deep learning. maybe even a 'dumbbed down' version for someone who is new to deep learning and convolutional neural ...
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0answers
57 views

Using a surrogate model for the solution space of an optimization problem

I have an optimization problem: Given a complex $n\times n$ covariance matrix $C$ one must find a complex $n$-vector $v_C^\ast$ which (approximately) minimizes an objective $f_C(v)$ over all space. $...
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10 views

Is there an archive of closed-form mutual information among the “famous” distributions?

I'm looking for a document or compilation table of closed-form mutual information as a function of their parameters, for known distributions such as normal, gamma, Poisson distributions. At least, I ...
2
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0answers
43 views

Multiple comparisons correction for dependent comparisons

In this blog post the authors discuss simultaneously estimating quantiles, and constructing a simultaneous confidence envelope for the estimation which covers the whole quantile function. They do this ...
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0answers
15 views

Are there any generally simple examples on Tabu Search in R?

I am looking for any examples of implementing Tabu Search in R. I know there is a package, but I would like to see if there are any good instructive examples where the code is built up and used to ...
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0answers
16 views

Maximum Likelihood estimator for GARCH with jump (papers on this topic)

Does anyone know a reference to a paper that would show an actual calibration of GARCH(1,1) model with jumps to a historical time series?
4
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1answer
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Do there exist adaptive step size methods for Newton-Raphson optimization?

Stochastic/Mini-batch gradient descent, caused by interest in deep learning, has made lots of advances in adaptive step sizes. For example, Adam, Nadam, Adamax, ..., are all improvements to the ...
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0answers
18 views

Ridge, Lasso or Elastic nets used in Accounting Research

I am trying to come up with ideas for my master's thesis and was wondering why literature on the above mentioned regression methods within Accounting Research is non-existent? I felt like the ...
0
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0answers
27 views

Introductory books on bayesian statistics with focus on normal distribution

I am searching for introductory books on bayesian statistics. Which Focus on normal distribution (Most of the books I came across through this answer focus on binomial distribution) Practical ...
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0answers
30 views

Confidence Intervals of not Gaussian functions

Is anybody know a good tutorial about how we calculate Confidence Intervals of not Gaussian functions? I give some example of what I kind of function I think about: 1st example: Let be $ X_1, X_2 \...
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1answer
84 views

state-of-art of ARIMA

Please, could you advice me a good paper which talks about the ARIMA's state-of-art? I have already searched on google but I have not found anything interesting.
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0answers
7 views

Software that finds correlations between loosely dependent time-series?

I'm not sure if this is the right kind of question for this site, so please let me know :) I'm looking for a time series data analysis platform, so I can take a collection of time series at 15-...
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0answers
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What are some easy to understand books for discrete stochastic process simulation using R?

What are some easy to understand books for discrete stochastic process simulation using R programming language? I mean for the starters?
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1answer
34 views

What's this class of algorithms called: (entire training dataset, new input) -> output?

Supervised machine learning algorithms normally work by preprocessing a training dataset and outputting a compact model (e.g. a bunch of regression coefficients) that can quickly give an approximate ...
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0answers
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What can I use to compute a similarity (or diversity) index for a sample with “multidimensional” attributes?

Current problem: We have a batch of $n$ items for which we capture their details with $m$ attributes. It could look something like this: The goal is to compute an "index" that says how "similar" this ...
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2answers
48 views

Easier than Element of statistical Learning and harder than Introduction to statistical learning

First of all, sorry for the bad english. I'm Asian. I'm majoring industrial engineering on a master's course. Recently, I've realized that I need to study statistical perspective on M.L so I'm ...
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22 views

Scalable kmean++ numerical example [closed]

I need a numerical example for computing the scalable kmeans++, since I'm not specialist in statistics and I didn't understand the messy greek letters in the algorithm. Any text reference link will be ...
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0answers
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Circular smooths within a GAM-GEE framework

I have a predictor variable which I fit in a GAM as a circular smooth term: ...
4
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1answer
67 views

Gauss Original Paper

I am looking for Gauss's 1809 paper in which he introduced least squares regression, MLE and the gaussian distribution. I cannot find it online. Can someone tell me where I may find it?
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1answer
13 views

How to generate a sanitized dataset using Differential privacy?

I'm learning about differential privacy. I understand the concept behind differential privacy, that you can add a small noise to the query to mask the true value using transformations like Laplace or ...
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0answers
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Biased estimates of Hurst exponent in R/S analysis

I've used the standard R/S algorithm for estimating the Hurst exponent in Mathematica*, and tested it on fBm and fGn for $H\in\{0.05,0.1,\ldots,0.95\}$, generating 1000 time series for each $H$. The ...
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1answer
43 views

Theoretical foundation for dropout in neural networks

Can someone point me to a thorough theoretical foundation for dropout in training neural networks? So far I have found only handwaving explanations (e.g. Goodfellow's textbook and the original paper) ...
4
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1answer
36 views

Poisson distribution and completeness, what happens when one point removed from parameter space?

Long time ago (early 1980's) my professor showed me a paper (I think it was Teachers' Corner or something similar) about the Poisson distribution and completeness. Showed that if only one point was ...
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1answer
25 views

Is there a freely available canonical reference for the standard R modeling paradigm

Bates, Mächler, Bolker, & Walker (2015) [assume] familiarity with the standard R modeling paradigm and cite a book (Chambers & Hastie, 1993, Chapter 4) as a reference. Is there a freely ...
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0answers
12 views

Geisser's definition of nonstochastic prediction

Does anyone have Geisser, 1993, "Predictive Inference: An Introduction." Chap- man and Hall, London. MR1252174? I am interested in the definition on page 31 for "nonstochastic prediction," but unable ...
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0answers
13 views

Standard Notation for Gaussian Measure?

There are standard notation for normal PDFs and CDFs, being $\varphi$ and $\Phi$, respectively. I would like to know if there is also standard notation for the Gaussian measure corresponding to a ...
3
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2answers
58 views

Bayesian Regression - Overview

Does anyone know a comprehensive, well-written and recent book / collection of articles about Bayesian regression and variable selection? The topics I am particularly interested in are: constraints ...
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0answers
12 views

How do you call line that marks success criterion?

In an example graph bellow, the doted line marks the criterion whether or not the model is successful. Only if all bars/dots are bellow that line, then the model is successful. What about the ...
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22 views

Dummy variable method for missing data in ML/predictive models

I'm looking for references on the use of zero-imputation with dummy-variable augmentation in the context of predictive models and MNAR missingness. Basically, the idea is that one imputes zero for ...
0
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0answers
8 views

A survey of different estimation methods (e.g. maximum spacing, minimum distance estimators, etc.)?

I recently learned about Maximum Spacing and Minimum Distance estimation methods and feel even more like I am not aware of even existence of a considerable portion of existing statistical methods. ...
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0answers
21 views

Concept of Stationary Population

In stationary population, there can be different probabilities for death in a given year for different age groups but these probabilities don't change over time. So the probability a 28 year old will ...
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0answers
14 views

Eigenfunctions heuristics for self-conjugate priors [duplicate]

Previously asked on math.stackexchange. I am looking for a citable reference (books, research papers, PhD theses, not websites, internal reports, etc.) about the heuristic interpretation of self-...
1
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1answer
17 views

When is the result of multidimensional-scaling unique up to isometry?

What conditions on the ambient space and/or the given matrix of dissimilarities guarantee that all point configurations that minimise the error function of multidimensional scaling (MDS) are congruent,...
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French website Providing Instruction/Tutorials on Statistical Theory

This is somewhat of an odd question for CV, but since it's a question about statistical education, I think it falls within the scope of CV. Several years ago I stumbled across a French website that ...
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3answers
35 views

Resources for hierarchical modelling in R

Just chasing a text/resource for learning hierarchical modelling in (and) R. I have extensive experience using Matlab and Stata but very limited R experience. Any recommendations? Happy to purchase ...
1
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1answer
30 views

Relationship between exponential families and moment generating functions

I have recently been playing around with some change of measure arguments for shifting the mean of a sub-gaussian distribution. It occurred to me however, that sub-gaussianity might not be the natural ...
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0answers
28 views

Independent Study Statistics/Probability Grad Level [duplicate]

I am trying to decide on topics for my independent study this semester. I am a Pre-Doctoral Mathematics student, so looking for a more math based text rather than engineering based (which I have found ...
3
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1answer
108 views

What can we say about distributions of random variables $X$ such that $X$ and its inverse $1/X$ have the same distribution?

What can we say about random variables such that it and its inverse have the same distribution? One example is Cauchy distributed random variables, easily proved via the fact that if $X, Y$ are IID ...
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1answer
22 views

Derivation of the Mann Whitney U normal approximation

The normal approximations for the Mann Whitney U statistic are given by wikipedia but there are no refrences mentioned. What are the actual derivation steps of the untied and tied case approximations? ...
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24 views

Asymptotic equivalence between cross validation and bayesian information criteria

I heard that Bayesian information criteria and cross validation are asymptotically equivalent when the size of validation set is large enough similar to the relationship between Akaike information ...
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2answers
103 views

Regression as mutual information minimization

I am trying to see if mutual information can be used as an objective function in a generalized formulation of the linear regression without the normal distribution assumption for the residual error. ...
1
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1answer
68 views

Most powerful test for deciding probability mass function

Let $X$ be an integer valued random variable supported on $\{0.1.2...,12\}$ whose pmf is either $g(x)=1/13; x=0,1,...,12$ or $ f(x)=\dfrac x {36} 1_{\{0,1,...,6\}} + (\dfrac 13 - \dfrac x{36})1_{\{7,...
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What are most recent research work on the problem of key phrases extraction from a text corpus?

I am interested in the problem of extracting key phrases from a text corpus. This is different from the keyword extraction problem, which is only for a particular document. This problem helps us, for ...