# 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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### 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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### 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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### 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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### 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 ...
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 ...
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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### 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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### 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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### 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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### 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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### (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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### 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) ...
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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### 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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### 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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### 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 ...
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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### 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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### 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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### 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 ...
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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### 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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### 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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### 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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### 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, ...
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, ...
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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### 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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### 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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### 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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### 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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### 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 ...
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: ...
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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### 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 ...
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 ...