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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25 views

Where is our consideration of "nuisance degrees of freedom" in modelling?

I am concerned about a lack of attention among researchers towards whether (or how) nuisance parameters affect degrees of freedom. For our purposes here we are considering $$\underbrace{\text{df}}_{\...
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Reinforcement learning based on change in discounted reward?

In RL systems that I know about, such as Q-learning or A3C, the agent makes a determination of discounted future reward as a function of the current observations or current internal state, and the ...
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Guide to self-starter estimators (parameter initialization) for "simple" functions

Background I have a collection of functions with trainable parameters that I am implementing as Keras model classes, which enables immediate use of a variety of objective functions, optimizers, and ...
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42 views

How to optimize a function with respect to a distribution, in the context of variational inference

Context: I am learning about variational inference. The reference I am following is linked at the end of this post. Goal: I want to learn how a marginal variational distribution $q_k$ is optimal in ...
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23 views

Measure-theoretically rigorous treatment of statistical learning theory

My main source on statistical learning theory has been Shwartz/Ben-David. This is a good book but it's a little vague from a measure-theoretic point of view. For example, in the definition of PAC ...
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27 views

Recommendations on litterature for classification problems [duplicate]

I am looking to further my knowledge of algorithms and regression methods for classification problems. What are some resources I should look at/read? Anything you can point me to would be of great ...
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26 views

Resources on on-line machine learning

I am wondering if there are any books/articles/tutorials about "on-line machine learning"? For example, this website has nice lecture notes (from lec16) on some of the aspects: https://web....
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2answers
85 views

Calculus for Statistics

If one were to learn calculus solely for the purpose of learning statistics, what should he focus on? If this is a ridiculous question and the honest answer is “All of it,” that is of course an ...
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Reference Request: Variational Expectation-Maximization algorithm for Latent Dirichlet Allocation with an added time component

This link has a pretty good runthrough on the variational inference (via variational E-M) for LDA with calculations expanded and explained. I am now considering a modified LDA which adds a time ...
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215 views

Age is given partly as a continuous and partly as a categorical variable

I have a dataset of the clinical information of 150 patients above 50 years old. I intend to do a logistic regression with it. (Presence of Symptom ~ Age, etc) From 50 years old to 69 years old the ...
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26 views

LASSO with $L_p$ norms for $1 < p < 2$?

For the sparse linear regression problem, minimizing the LASSO objective $\| X \beta - Y \|_2^2 + \lambda \| \beta \|_1$ is known to recover the optimal data generating parameter $\beta^*$ with the ...
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30 views

Books on Test of Hypothesis

I need some good intuitive books on Test of Hypothesis.I am an undergraduate student and I didn’t find any intuitive books on this topic.
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Constructive learning models that can run (predict) fairly well on a Raspberry pi?

I'm looking for a model that is based on constructive learning and will do it's predictions live (via video camera) on the Raspberry Pi 4 Model B, either trained on a PC or pre-trained, I found out ...
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27 views

References for PCA analysis eigenvalue cut-off (eigenvalues > 1)

I frequently see PCA tutorials that guide us to use principal components with eigenvalues > 1 (e.g., https://www.reneshbedre.com/blog/principal-component-analysis.html). But, I cannot find the ...
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51 views

Does the margin of a classifier scale with the dimension of the problem?

Consider a binary classification problem on $\mathcal Z=\mathcal X \times \mathcal Y $, where $\mathcal X$ is some subset of $\mathbb R^d$ and $\mathcal Y = \{-1;1\}$. You have a dataset of $n$ ...
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18 views

Maximum likelihood estimation when the model is misspecified (and the true data generating process is a mixture model)

I'm interested in the properties of maximum likelihood estimators under a particular form of model misspecification: We observe data $\left\{X_i\right\}$ generated from a finite mixture model Let $\...
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Are randomness and probability really logically dependent notions?

Background Some have lamented that it is difficult to distinguish randomness from probability, but I seem to be having a contrary difficulty: are they even logically dependent notions? Probability ...
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Do the robust standard errors in GEE also protect you from a skewed errors

I have a numeric outcome with repeated measures on individuals and several predictors. The basic analysis is linear regression, but with consideration of random effects or GEE to adjust for the ...
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2answers
31 views

Inference: How is the Laplace approximation actually useful to us compared with MLE and MAP?

I was reading a few different sources (including the "Machine Learning and Pattern Recognition" book by Bishop) about the Laplace integral approximation method for inference. However, I am ...
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21 views

Does blind source separation (ICA) work if channels of mixture are observed asynchronously?

Does Independent Component Analysis (ICA - fastICA, SOBI, etc.) work reliably when applied to a multidimensional mixture (observation) $X = (X^1, \cdots, X^d)$ if the different channels $X^i$ of the ...
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34 views

Where is a good place to start with (hidden) state-space models?

I'm interested in (hidden) state-space models. My language here might be poorly articulated as I'm quite new to this area of math. The topic of Kalman filters has come "across my desk" a ...
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211 views

Textbook recommendations covering machine learning techniques for causal inference?

Over the past 15 years there has been progress in adapting machine learning methods for causal inference. For example: targeted learning, double machine learning, causal trees. Is there a textbook ...
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15 views

best books for introduction time series [duplicate]

I am a beginner because I need a book to learn time series. please guide me
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1answer
65 views

Literature on Noninformative Priors for GPD

I am starting to do some work using the Generalized Pareto Distribution (GPD), and was hoping someone might be able to point me in the direction of literature (or just general recommendations) on ...
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1answer
47 views

Hidden Markov Model with Probabilistic Observations

I have an HMM with $N$ states and $T$ possible obsevations where $A \in \mathbb{R}^{N \times N}$ is transition probability matrix and $B \in \mathbb{R}^{N \times T}$ is emission probability matrix. I ...
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1answer
23 views

derive multivariate pdf from matrix variate pdf

I am working on the proof part in Definition section of https://en.wikipedia.org/wiki/Matrix_normal_distribution. I can understand what s going on, except for the last part how inv(V(kron)U) becomes ...
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1answer
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Need data preparation cheatsheet / guidelines / first principles to train team members! [closed]

Really ran out of ideas and hence such a basic question to the community - Despite the repeated emphasis on ensuring data accuracy/validity, team members just do not spend enough time on it because ...
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Semiparametric theory worked examples

Does anyone know any resources for worked problems in Semiparametric theory? I'm currently reading Tsiatis 2006 and am looking for examples. Thanks!
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1answer
58 views

Statistical model for quantities that add up to 1

I want to create a model for quantities $z$ that live in a probability simplex, that is, they are nonnegative and always add up to 1: $$ S = \left\{z \in \mathbb{R}^{k} : z_1 + \dots + z_{k} = 1, z_i \...
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1answer
25 views

Any recommendations for books on CFA and SEM, R?

Context: -Psychology student interested in learning more about CFA and SEM with the use of R. Recommendations appreciated.
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38 views

Easy to follow video lectures or online help on measure-theoretic mathematical statistics

Due to some unexpected events, I was not able to follow my measure-theoretic mathematical statistics classes for a while and now I have to cover these materials (chapter 1 of Jun Shao's book and ...
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26 views

I have been told that lmer performs poorly with non-normal outcomes, and recommended nlme over lme4. Is nlme more versatile than lme4? [duplicate]

Someone who I consider an expert and very knowledgeable in mixed models has referred to Grimm, Ram, & Estabrook's "Growth Modeling: Structural Equation and Multilevel Modeling Approaches"...
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46 views

Areas of research in statistical machine learning

I'm reading from a book called Machine Learning: A Probabilistic Perspective by Kevin Murphy. Besides being somewhat challenging to understand, I feel that the earlier chapters (on probability, ...
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3answers
140 views

Is there some good references of the method Median of Means Estimator?

I can't find the term in Wikipedia, and by searching online, I seem to know the original material raised up the idea Median of Means Estimator is this book, while I can only find the scanned edition ...
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1answer
249 views

How can I learn statistical a/b testing?

I need to learn statistical a/b testing. I have machine learning and probability background, how can I learn about this topic? Which books should I read? Or maybe someone has article suggestions?
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1answer
47 views

Biostatistics book suggestion

I am a statistical programmer and am working on SAS in a pharma company. Also I have masters in statistics and have interest in the subject. Can anyone suggest me books on biostatistics, helps in SAS ...
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51 views

Is there a Feynman Lectures equivalent in statistics?

I am looking for statistics books that give a good comprehensive overview of the subject, including all its main and mature areas. Something like these equivalents in mathematics: Mathematics: Its ...
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24 views

Recommnedation for books and material for solving differerntial equations through neural networks

I was going through some past and recent papers on using neural networks for solving ordinary and partial differential equations. One of the fascinating papers that inspired a flurry of papers is ...
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1answer
52 views

Are there any automatic pattern recognition algorithm for integer series?

I am looking for an algorithm, that given an input such as 1, 2, 3, 4... would output either " f(x_n) = n " or at least continue the series and give a "5". I know this can be done ...
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19 views

What’s a textbook covering similar content to “Introduction to Probability Models” by Sheldon Ross?

I’m taking a class with a instructor using said textbook, and I find the explanations in it lacking. It’d be great if anyone can offer an alternative book covering similar content (i.e. conditioning ...
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1answer
31 views

What type of statistical inferences are possible on aggregated tables?

I have a table with the following format CountH SubcountH1 SubcountH2 CountK... VarA SubA1 SubA2 SubA3 VarB SubB1 SubB2 . . . The table is filled with ...
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25 views

Difference between discriminant analysis and neural network (one layer)

So I am doing some research on this topic and I "hit a wall" with this question. I managed to find some papers on using DA vs NN on data but i didn't find anything math related. Maybe ...
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0answers
28 views

Summarization and resources for Bayesian decision theory

Looking for textbooks and/or resources to get familiar with Bayesian decision making. I have the book, Statistical Rethinking, by Richard McElreath and I've found this to be a really great resource ...
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20 views

A reference on statistical pattern recognition with solution manual

I'm taking a graduate course on statistical pattern recognition in the upcoming semester. I was wondering if there's a reference book with a worked solution manual, to make learning the course easier? ...
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17 views

Ways to calculate proximity score in a social network

I'm looking for the most correct way to calculate a proximity score between users of a social network (Twitter). There are 100 users who replied, mentioned, and liked each other. I want to aggregate ...
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2answers
244 views

After "Statistics" by Freedman, Pisani, and Purves what book is good for ANOVA?

I have a tiny bit of probability under my belt so far using the excellent "Introduction to Probability" by Anderson, Seppalainen, and Valko. I am still working through it. Next up is "...
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19 views

NN for resource management of an VM

Are there any papers/projects that deal with neural networks learning/adaptation for resource management (learning of system behavior and resource adaptation such as memory, CPU for an VM)? e.g. some ...
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0answers
20 views

Book recommendations for Applied Statistics [duplicate]

Any good books focussed on applied statistics for self-study? If the book works with Python it'll be better for me. I'm a Physicst with a Master in Science degree, but I don't want a rigurous book on ...
2
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1answer
52 views

A front-loaded Gumbel-like distribution

I'm looking for a distribution that is somewhat like the Gumbel distribution and I was wondering if anyone could help. The parameters are a positive integer $n$ and real numbers $\mu>0$ and $\sigma&...
3
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1answer
267 views

What are relatively simple simulations that succeed with an irrational probability?

What are relatively simple simulations that succeed with an irrational probability? Let me break down this question. Relatively simple simulations. By "relatively simple" I mean simulation ...

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