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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1answer
16 views

What are the conditions of applicability of linear regression? [duplicate]

I am looking for a list of "Conditions of applicability of linear regression" to finish a work, but I cannot find any reference of this in any book. I founded something in several links, but in one ...
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1answer
28 views

What to do with statistically insignificant dummy/categorical variables? [duplicate]

From the research I've done the common answer is that you can not remove insignificant dummy variables from a regression. I'm having a hard time finding academic papers or books that back up this ...
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2answers
46 views

recommendation for humor book on statistics [closed]

I am looking for a humor book on statistics. The intent is not to learn statistics. I am rather thinking about funny statistical facts, funny statistical quotes, etc. Any recommendation?
13
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1answer
226 views

What is the support vector machine?

What IS the support vector machine? Can someone clarify my confusion? Possible answers: The SVM is the problem: given data $(x_n, y_n), n = 1, \ldots, N$ $$\min_{w, b}\frac{1}{2}||w||^2$$ $$\text{ ...
2
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2answers
68 views

Who “invented” the standard error of the mean?

I need the earliest available source. I already searched statistic books of Andy Field, Bortz & Schuster, Rasch & Friese, Wikipedia, Google and I asked 3 colleagues who teach statistics.
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0answers
35 views

Inventor of null hypothesis significance testing?

NHST is universally most used method of scientific inferencing. When was it first described in its current form and when was it first time used in the medical research? This info seems to be hard to ...
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0answers
10 views

Sources for panel data on German house prices [closed]

I'm looking for sources for panel data, preferably a database, on German house prices, it doesn't have to be free, but nothing expensive. I've tried the federal government database, but I just can't ...
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0answers
73 views

What is the “direct likelihood” point of view in statistics?

I am reading a Springer title from 1997 called Applied Generalized Linear Models by James K. Lindsey. In the preface, Lindsey writes For this text, the reader is assumed to have knowledge of basic ...
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0answers
17 views

Relationship between repeated measures ANOVA and random / mixed effect models

This is not concrete question but more a conceptual one, although a pretty low-level one I guess: When I was taught ANOVAs the 'classical' sums of squares way, I was told that repeated measures can ...
3
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2answers
85 views

Most mathematically rigorous books to learn statistics from? [duplicate]

Assume the math background is not an issue. Which books would you recommend as the most mathematically rigorous to learn mathematical statistics at the graduate level? Does Kendall's Advanced Theory ...
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2answers
25 views

What are good books for learning linear models with Python and R?

Not sure if there's a book recommendation section. I am looking for two books, one for implementation in R and one for implementation in Python. I'm hoping the books go pretty in depth on building ...
2
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3answers
122 views

Condition “Sample size > 30” for infering population proportion or mean [duplicate]

One of the conditions to use statistical inference, when estimating the proportion of a population based on the sample proportion, is that: The data's individual observations have to display ...
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2answers
14 views

What does residual mean in the context of minimizing a function?

equation 1.2 in PRML: pattern recognition and machine learning denotes the sum of the squares of the errors between the predictions $y(x_n,w)$ and the corresponding target values $t_n$. $w^*$ ...
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0answers
15 views

Research on explaining generalizability of deep learning methods

I've read a few classic papers on different architectures of deep CNNs used to solve varied image-related problems. I'm aware there's some paradox in how deep networks generalize well despite ...
4
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1answer
349 views

Has anyone studied linear regression where the covariance matrix of the error is a function of the parameters being estimated?

Consider the multivariate linear model: $$y = X\beta + e$$ $y$ is the measured output, $X$ is the model matrix, $\beta$ is the parameter vector, and $e$ is the zero-mean error vector: $$E[e] = 0 \...
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0answers
16 views

reference request for the impact of priors in bayesian statistics

It is well known that in bayesian statistics, the prior believe can have a large impact on the estimation result. For example if you flip a coin ten times to determine whether it is loaded, a prior $...
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0answers
15 views

First historical references on auto-correlation and cross-correlation

Although the origin of Pearson's correlation coefficient is well documented (see wikipedia), I have trouble to find some of the first and historical papers introducing the motivation, the benefits and ...
3
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1answer
35 views

Book recommendations on how to conduct simulations in the context of OLS and Structural Equation Modelling

The title really says it all. Does anyone have any recommendations for well-written books, preferably with plenty of examples, on how to conduct simulation studies in the context of OLS and Structural ...
3
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2answers
65 views

Learning from multiple very varied data sets?

Suppose we have a set of objects $X$ (e.g. individual humans). Suppose also that humans can be described by a set of (potentially very high-dimensional) variables $V_i$, (e.g. $V_1$ is a picture of ...
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1answer
60 views

Learning problem when we have data from distributions $(p_i)$ when we care about (known) distribution $p^*$?

Suppose we have a dataset $D$ or multiple datasets $(D_i)$, with distributions $p_i:X\to \mathbb R$. Suppose there is another distribution $p^*$. All distributions are known, including $p^*$, but the $...
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0answers
13 views

Reference request: statement about jointly Gaussian RV

I found a theorem online https://people.eecs.berkeley.edu/~ananth/223Spr07/jointlygaussian.pdf Is there a secondary reference for this theorem?
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1answer
29 views

What are some books that explain the origins of or principles behind common statistical methods?

A friend of mine asked whether I knew of such a book that offers both intuitive and formal explanations of how a wide range of statistical methods were originally derived. She wasn't looking for a ...
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1answer
29 views

Unequal variance in randomized experiments to compare treatment with control?

Consider a randomized experiment to compare (one or more) treatment(s) with a control. Since groups are defined by random assignment, we should expect equal variances for a null-experiment (that is, ...
2
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0answers
14 views

Signal-to-noise-ratio, Fisher information and and “estimability”

Given a parametric statistical model, is it common to study the quantity $$ Q_{\theta} = \theta^2 I_{\theta} \, ,$$ where $I_{\theta}$ is the Fisher information? (I focus on a single parameter for ...
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1answer
44 views

Choosing among recent references on Machine Learning

For personal reasons, I need a recent reference book on ML which is not mainly focused on programming, such as for example https://www.amazon.com/Hands-Machine-Learning-Scikit-Learn-TensorFlow/dp/...
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0answers
28 views

(Teaching) references for computational complexity

Background: I am going to teach computational complexity (time complexity) within an introductory course in machine learning. I would like to gently introduce the notion of computational complexity ...
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0answers
10 views

Prerequisites for reinforcement learning for DTR

I want to learn how RL is used for Dynamic Treatment Regimes. What are some must-read articles or papers? Also, I am relatively new to RL and am currently reading Sutton's book on the topic. Lets ...
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0answers
69 views

What is topological statistics?

I came across Carnegie Mellon's Topological Statistics website, and it greatly piqued my interest. What exactly is Topological Statistics? Is it a subfield of statistics? What background (stat, math, ...
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1answer
53 views

What's a good textbook with lots of real life examples on GLM and statistical inference?

I am teaching myself statistical inference, and now I am learning about generalized linear models. I am looking for lots of serious examples to work on. I want to make sure that my understanding is ...
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1answer
26 views

Book recommendation for analyzing and preparing data for machine learning

I have a school project in which I need to apply several supervised learning algorithms over a data set. Is there a good book that you recommend that focuses on data preparation, like: zero values, <...
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1answer
27 views

Self-organising Neural Network - Looking for litterature

I am looking at developing an algorithm that would automatically grow the structure of a neural network by adding/deleting units within a layer, or adding layers as necessary. I researched the topic ...
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2answers
54 views

Lecture notes on statistics and probability [closed]

Can you suggest some good introductive lecture notes, books and papers on statistics and probability? thank you, I appreciate it very much.
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1answer
18 views

Can we test Variational Autoencoders with deterministic $z=0$?

Let's say we want to compare a vanilla Autoencoder to a Variational Autoencoder. The first one gives a deterministic output which basically represents the output with the highest likelihood. When we ...
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1answer
26 views

References on frequentist hypothesis testing

I am looking for some references on frequentist hypothesis testing (e.g., t-test, chi-squared test, F-test, A/B testing etc). I have significant experience with probabilistic methods like Bayes rules, ...
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1answer
36 views

Statistics book for Machine Learning [duplicate]

Hello I am a mathematician currently studying Data Science and I would like to ask for a book that can give me a variety of statistical tools for having more solid conclusions in my analysis of a ...
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0answers
22 views

Simplifying XGBoost

I need to explain the concept behind XGBoost to a few people. Although I understand how it works, I'm looking for a good analogy using which I can easily describe XGBoost. Probably something which ...
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0answers
44 views

Expected value for f(x) [closed]

I am reading an article and trying to extend their case to a multivariate case. I have the function $f_{i} (x)=\frac{1}{|Σ|}f_{0}((x-μ_{i})'Σ^{-1}(x-μ_{i}))$, where $f_{0}(.)$ is a base density ...
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0answers
21 views

“Simple” boundary correction method in kernel density estimation

I'm new to kernel density estimation and have a rough idea on boundary bias. When correcting for boundaries, I tried to use boundary correction method as "simple" which is available in R. Once I ...
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1answer
32 views

Literature on Bayesian stuff with Normal Distribution? [closed]

I am writing something on Bayesian Analysis involving the normal distribution. I know that the conjugate prior is the so-called normalized Gamma inverse distribution, I know the update rule for the ...
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0answers
25 views

Properties not yet proven for neural networks but proven for regression

This question is a bit vague: Are there any properties postulated for feed-forward neural networks which are not yet proven and have a known analogue in classical linear regression analysis?
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0answers
7 views

Reference request: Table of probability mass function / probability generating function pairs?

I have a probability generating function $G(z) = \sum_{k=0}^\infty z^n p(n)$ for a discrete random variable which is somewhat complicated. I would like to "invert" it to obtain the pmf $p(n)$, which ...
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0answers
14 views

Extension of Potts model with non-constant interactions?

Is there any work that extends (allows) Potts model to have non-constant interactions between the lattice points? Specifically, the interaction matrix is a symmetric matrix that can have both positive ...
3
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3answers
120 views

Regression model with aggregated targets

Similar as in this self-answered question, I want to ask about possible approaches for modelling data with aggregated targets, i.e. things like $$ \bar y_{j[i]} = \alpha + \beta x_i + \varepsilon_i $$...
14
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2answers
313 views

Literature review on non-linear regression

Does anyone know of a good review article for the statistical literature on non-linear regression? I am primarily interested in consistency results and asymptotics. Of particular interest is the ...
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0answers
11 views

How to start with ARIMA? [duplicate]

Which book or standard procedure to read first? My basic want is to start on Time-Series Analysis. I need to understand ARIMA from beginner level and be able to answer basic questions on it.
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0answers
44 views

Who to attribute information gain to?

I am writing a paper where I examine information gain specifically with regards to feature selection and am wondering what the proper reference should be. I have looked all over and I can't find a ...
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0answers
39 views

error in the book “A first course in Machine Learning”?

I am reading the book "A first course in Machine learning". At page 74 when talking about the maximum likelihood solution, considering the data matrix X 2x2, he ...
0
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1answer
88 views

Batch Normalization or just z-normalization as a Nonlinearity

It is already common to do something "like"**(see asterisks below) z-standardization of the outputs of one neural network layer before passing it to the next. z-standardization would transform the ...
0
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1answer
62 views

Decide for three Bernoulli samples are some of them from the same distribution (or non of them) ? (do not use t-stat ) [duplicate]

Please pay attention, I am interested in Bernoulli samples, and hope to find criteria specific to Bernoulli distribution, not using s Student's t-statistics or Mann-Whitney or etc., since their use ...
2
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1answer
90 views

What does one expect from a great course of time series? [closed]

I usually teach finance (asset pricing and equilibrium models), quantitative economics (linear algebra and optimization), econometrics, computer science introduction to programming and machine ...