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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Risk of Spurious Relationships As a Function of 3 Magnitudes: # Times Sampled, # Individuals Sampled and # Variables Measured

I've seen some literature that quantifies the risk of spurious relationships in terms of sample size vs number of variables but I've not seen literature that quantifies the risk based on all 3 ...
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23 views

Fisher information matrix and gradients

I'm a math Ph.D. without formal training in statistics. Quite a few papers on normalization methods in deep learning mention the Fisher information matrix and how it's related to the Riemannian metric ...
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1answer
32 views

Suggested books to study statistics [closed]

I am doing a research that requires me collecting and analyzing data samples in order to identify if there is correlation or no with respect to some parameter. I am looking for the best resources to ...
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2answers
50 views

Best resources on imputation in R [duplicate]

This is my first question at stats. I need to impute some factors and numbers in my data set in R. What are my best options regarding packages and also a source to read more about the theory.
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37 views

Where to learn the theory behind common statistical techniques [duplicate]

I'm a college student and pursuing (in part, at least) a statistics and data science track. Much of my coursework beyond the introductory statistics sequence has involved topics like multiple ...
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14 views

Wilks' lambda's exact distribution when one of the parameters is 1 or 2

Citing Wikipedia, From the relations between a beta and an F-distribution, Wilks' lambda can be related to the F-distribution when one of the parameters of the Wilks lambda distribution is either 1 ...
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1answer
272 views

Statistical analysis applied to methods coming out of Machine Learning [closed]

Most of the recent famous methods coming out of the machine learning, are supervised learning methods like Decision Trees, Random Forests, Deep Learning, SVMs. The more traditional supervised ...
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40 views

Looking to identify a book by a top statistician with a chapter on Simpson's Paradox

It was more than 20 years ago. I had just gotten acquainted with Simpson's paradox. I was browsing in a bookstore and saw a book by an eminent statistician -- eminent in the sense that I had come ...
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1answer
17 views

marchenko pastur for Correlation

It has been suggested to me that if I construct a covariance or correlation matrix using factor model then I can use the Marchenko-Pastur distribution to highlight significant correlations (or ...
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11 views

Phase marginal for a multivariate complex Gaussian density

Suppose $z$ is a random variable taking values in $\mathbb{C}^n$ and admitting the complex Gaussian density $p(z;W) \propto \exp{(-\frac{1}{2}z^*Wz)}$, where $W$ is Hermitian. Let $r$ be the vector of ...
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2answers
193 views

Finding the MLE of Poisson in R [closed]

I'm trying to determine the MLE of $\lambda$ in a Poisson distribution using R. I'm aware that the MLE is $\hat{\lambda}=\bar{x}$ but I want to demonstrate this using Rmarkdown. My experience with R ...
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12 views

(Existence part of) Neyman-Pearson via weak-* convergence

I would like a ask whether there is any statistical reference containing the following functional analytic argument for the existence part of Neyman-Pearson: Let $(R, \mathcal{F}, \mu)$ be a measure ...
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24 views

Correspondence between time series models in continuous vs. discrete time

I am interested in an overview over the connection and correspondence between time series models in continuous vs. discrete time in finance. E.g. take ARMA(p,q) or GARCH(s,r) or ARMA(p,q)-GARCH(s,r) ...
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1answer
64 views

Best Course of Study for Data-Science/Statistician Interviews [closed]

This is my first question here, so please pardon my gaffes. I am currently working as a Data-Scientist, a position which I worked up from Junior Analyst position.My bachelors is in Computer Science ...
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1answer
41 views

Scientific papers using “entry” level Econometric procedures

I am studying Econometrics on a Masters' level. I have a pretty good grasp of the theoretical aspect of different processes, from dummy variables to time series, stationarity or simultaneous models (...
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1answer
47 views

Books for self-learning about statistic Simulation?

Preferably an introductory book, i.e. for undergrad (or notes or something like that) that explains concepts with detail and with lots of examples, without losing the formality. That covers the ...
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1answer
64 views

Best book for statistical inference (Self-study) [duplicate]

I want to develop some skills in statistical inference for a career in data science or machine learning. I purchased the book "All of Statistics" which is a good book, but there are not answer keys ...
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1answer
23 views

Reference request: initializing big neural networks with small neural networks

I am currently trying some meta-algorithms on training neural networks. Start with a small but expressive enough network for training and after several epochs, initialize a larger neural network with ...
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24 views

Are there extant deep learning analogs to random coefficient (aka mixed) models?

Random coef models, applied to longitudinal data, capture response heterogeneity by cross-sectional unit. I've got a longitudinal prediction problem, in which I know that some "features" (or ...
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1answer
40 views

Seminal works in deep learning [closed]

I'm compiling a list of 7 seminal works in deep learning to work on during 14 week semester course. I'd appreciate if you suggested papers for the list. I'm looking for the papers that impacted the ...
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9 views

SEM resources from a linear model prospective

I'm starting a new project at work that requires theory and application of structural equation models, but my background is quite low in this area. I have a very good background in regression, linear ...
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1answer
29 views

Kolmogorov Distribution D statistics

As far as I have searched the cumulative distribution function of 𝐾, asymptotically (kolmogorov distribution) is given by Pr(𝐾≤𝑥)=1−2∑∞𝑘=1(−1)𝑘−1𝑒−2𝑘2𝑥2=2𝜋√𝑥∑∞𝑘=1𝑒−(2𝑘−1)2𝜋2/(8𝑥2). But ...
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94 views

Does High Dimensional Data effects SVM?

As we move into higher dimensions, we will find even more corners. This will make an ever increasing percentage of the total space available. Now imagine we have data spread across some ...
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71 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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1answer
41 views

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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1answer
14 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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19 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, ...
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94 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, ...
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2answers
65 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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66 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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16 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 ...
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179 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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63 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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1answer
20 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?
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1answer
91 views

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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23 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 ...
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51 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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31 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
94 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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8 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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9 views

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
39 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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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
98 views

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

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 studying the book Introduction to statistical learning ...
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23 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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1answer
51 views

Circular smooths within a GAM-GEE framework

I have a predictor variable which I fit in a GAM as a circular smooth term: ...
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1answer
86 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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39 views

Best approach for learning Reinforcement Learning coming from economics?

I have an economics background so I have have Calculus, Linear Algebra, Diff. Eq., 2 semesters of Stats and Prob. and some Python Knowledge. My school offers a 2 months postgraduate course in ...
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1answer
49 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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95 views

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 ...