"References" is our generic tag for questions seeking information about books, papers, presentations, videos of lectures, on-line tutorials, etc., regarding any subject matter that is on-topic for Cross Validated.

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2
votes
1answer
26 views

A reference for Pearson's chi-squared testing

I am wondering if there is a reference for the Pearson's chi-squared test suitable for technically-sophisticated audience that simply presents when the test (in its various forms) is appropriate and ...
0
votes
0answers
16 views

Beta linear model

I wanted to learn more about the Beta linear model for data analysis. I was wondering if there were any good books out there to help code this model in R and to learn more about the Beta linear model. ...
3
votes
1answer
24 views

How to interpret confidence interval with accuracy phrase

Upon reading a peer reviewed article, I found this: A Chi-square test shows that the demographic characteristics of the sample represent Toyota GB’s hybrid customers (data obtained from the New ...
8
votes
2answers
266 views

Best suggested textbooks on Bootstrap resampling?

I just wanted to ask which are in your opinion the best available books on bootstrap out there. By this I don't necessarily only mean the one written by its developers. Could you please indicate ...
2
votes
1answer
58 views

How to regress two categorical variables

I'm not looking for a detailed answer, just some pointers towards possible things I could read to better understand this problem. Let's say that we have a survey that asks two questions, $X$ and $Y$. ...
3
votes
0answers
51 views

Paper showing that logistic regression intercept biased in rare events

I'm studying the logistic regression for estimate the Probability of Default of SME's. Fortunately the event (firm's default) is a rare event. King and Zeng tell us that "logistic regression can ...
1
vote
0answers
13 views

Generalization of Fisher information for a discrete parameter

This is mainly a reference request. There must be some generalizations of the concept of Fisher information for discrete (say, integer-valued) parameters, and of related results such as the ...
3
votes
0answers
33 views

Meta-analyses for variance rather than means

What are the main complications / differences when conducting a meta-analyses where the metric of focus is not effect size (i.e., means) per se, but instead estimates of variances from models? Nods ...
6
votes
2answers
166 views

Data transformation using copulas

I've heard about the use of copulas to transform data. For instance, supposedly it's applied to data that is non-normal to make it look more normal. However, I don't quite understand how this is done. ...
1
vote
0answers
11 views

Coarse-resolution subsampling of time-series data

Suppose I have time series data with a very fine resolution, e.g. 100 datapoints per second. I want to report this data to some service that can only take data at 1 point per second. I need to do ...
3
votes
0answers
45 views

Recommendation for books/notes for linear mixed effect models for longitudinal data?

I'm a beginner in data analysis who needs to learn (say in a period of 2 to 3 weeks or so) the key ideas and techniques in the linear mixed effect models for longitudinal data. I'll apply them in ...
6
votes
3answers
593 views

Can mean plus one standard deviation exceed maximum value?

I have mean 74.10 and standard deviation 33.44 for a sample that has minimum 0 and maximum 94.33. My professor asks me how can mean plus one standard deviation exceed the maximum. I showed her ...
0
votes
0answers
28 views

Generalized likelihood ratio test

Does anyone use the generalized likelihood ratio test for detecting a sudden change in time series forecasting (ARIMA Model)? A paper by Bonne Zhu uses this technique for anomaly detection, but I ...
0
votes
0answers
22 views

Machine Learning books for CS (non-statistician) grad student [duplicate]

What books on machine learning are recommended for a CS graduate student without a huge background in statistics? I do have some background in ML (and of course linear algebra, probability, etc.) but ...
0
votes
1answer
29 views

How to transform non-Gaussian multivariate time series

I wish to apply a VAR-like kind of model to a multivariate time series dataset. The model assumes that $X_t | X_{t-1} \sim \mathcal{N}(\Gamma X_{t-1},\Omega)$ for $X_t \in \mathbb{R}^p$. I want to ...
1
vote
0answers
9 views

How can parameter expansion be applied to cox proportional hazard models with random effects?

Parameter expansion is used in various GLMMs to accelerate e.g. EM or Gibbs convergence. Is anybody aware of a paper/work which implements PX for CPH?
0
votes
1answer
12 views

Embedding Markov Matrix

A stochastic matrix with states $S_1$, $S_2$, $S_3$, $S_4$ is given, now we would like to build up another stochastic matrix with finer states, meaning that the states $S_1$ will be considered as ...
0
votes
3answers
41 views

What to do when some categories have too few observations

I have an ordinal, categorical variable with five levels, of which the last two have only one observation for each. Should I leave them alone, omit them, incorporate them in another category, or do ...
0
votes
1answer
25 views

References for Probit and Logistic Regression

I am looking for a book that essentially covers probit and logistic regression. Any suggestions?
0
votes
0answers
50 views

Recommend textbook for probability theory and stochastic process

Would you mind recommend a textbook for the following topics? It's a graduate level course for students in finance/economics. Probability theory (no measure theory please) Conditional expectation ...
4
votes
1answer
140 views

Can anyone provide a peer reviewed reference for the calculation of least squares means as implemented in the R package lsmeans?

I am using the lsmeans package from the R programming language for follow up analyses of a linear mixed model. However, my target journal does not generally use these methods and I would like to have ...
1
vote
0answers
15 views

best theory on fitting mixture of gaussians

What are the current best results on fitting mixtures of Gaussians with any algorithm (EM or something fancier)? Specifically, if I know only the number of components, what are the sharpest sample ...
0
votes
0answers
39 views

Request for reference for longitudinal data analysis which is mathematically well-written

I'm a person with graduate level mathematics and some undergraduate statistics background, who'll have to study some basic longitudinal data analysis. I've studied the basics of correlation and ...
0
votes
0answers
19 views

Requirements of text-sources for most promising results with Latent Dirichlet Allocation (LDA)

I was wondering if there are any papers about the efficiency of the LDA in terms of human reception in relation to the document-type. Resprectively, are the topics that LDA finds for books, ...
10
votes
3answers
527 views

Introductory texts on structural econometrics

In recent years the structural approach to econometrics compared to reduced form econometrics has become more popular. This involves tight combination of theoretical economic models and statistics in ...
0
votes
0answers
23 views

Regression using a priori knowledge

I am sorry if the title (and probably the question) is not very clear but I have a regression problem which might be a bit over my head if I want to do it well. I am only interested in getting some ...
0
votes
0answers
16 views

linear discriminant analysis, Bayes approach authors?

I know that in 1936 Fisher proposed the LDA that minimizes the variance within and maximizes between. My question is, the Bayes approach of LDA is attributed to a particular(s) author(s)? and what ...
3
votes
0answers
43 views

Tracy-Widom distribution - Phase transitions - catastrophe/chaos - 'surface-fit'/'curve-fit' software

Is there an algorithm to determine the fit of a sample set of data to a saddle curve? I'd like to know the variance from the closest fit the sample has to: \begin{align} z &= x^3 - 3xy^2 \\ z ...
3
votes
0answers
38 views

Where to start to learn about pricing models?

I have a situation at my work that I want to take as a chance to learn more about pricing and stats. In a nutshell, I work for a company that buys several products and then charges a margin (we have ...
6
votes
2answers
98 views

How do I cite the iris dataset in a paper?

I want to use the iris dataset provided by scikit-learn for a paper. But I don't know what the standard for referencing datasets is. What citation should I use for this dataset in my paper? Should I ...
1
vote
2answers
54 views

Ratio of CDFs $F(x)/x$ property

In my research project is useful to classify cumulative distributions functions of random variables with support in $[a,b]$ with $0\le a<b\le+\infty$ depending on whether the ratio, ...
0
votes
0answers
20 views

What books to read for Biostatistician position supporting product develpment for in -vitro diagnostics?

This is not a question concerning a specific statistical method, but I need an advice. I am interested in a position as a biostatistician to support product development for in-vitro diagnostics. I ...
1
vote
1answer
54 views

The sum of the kernel density values is not 1?

>> x = [randn(30,1); 5+randn(30,1)]; >> [f,xi] = ksdensity(x); >> sum(f) ans = 5.5376 I ran the ...
2
votes
1answer
37 views

Is there an article/book reviewing different methods for constructing posterior point/interval estimates?

Given a one-dimensional posterior distribution it is often the case that you want to calculate a point estimate and a credible interval for the corresponding parameter. There are, of course, many ways ...
6
votes
1answer
37 views

Reference for the idea that a simpler model can be used when the range of data values is smaller

When we build a statistical-physical model, generally, a simpler model can be justified when the range of data-values is smaller. I can't be the first person to use this idea, but I also can't find ...
0
votes
0answers
30 views

Statistical learning theory

I am looking for some good books for statistical learning theory. For an introduction I went through "An elementary introduction statistical learning theory Kulakrani" It was a good read with less ...
6
votes
2answers
128 views

Example of an inconsistent Maximum likelihood estimator

I'm reading a comment to a paper, and the author states that sometimes, even though the estimators (found by ML or maximum quasilikelihood) may not be consistent, the power of a likelihood ratio or ...
2
votes
3answers
137 views

Rigorous real analysis book for probability theory

I have a Masters in math and I am currently doing a Masters in statistics. I am disappointed at the level of rigor in the proofs (and often outright omission of the proofs just a statement saying "in ...
0
votes
0answers
10 views

Introducing binomial distribution as a sampling distribution over Bernoulli distribution

In many introductory applied statistics text books and curricula, study of basic probability distributions begin with binomial distribution. I think it would be pedagogically beneficial to introduce ...
4
votes
2answers
87 views

Is Hurlbert 1984 the best introductory overview to pseudoreplication?

I often find myself explaining (or wanting to explain but not wanting to be boorish) the basics of random sampling and the consequences of pseudoreplication, specifically the limitations and ...
1
vote
1answer
44 views

What criteria should be used in selecting a statistics book?

In his paper "Mindless statistics", G. Gigerenzer unfavourably cites several statistics books. One of the things prof. Gigerenzer mentions is the fact that the books do not mention various approaches ...
14
votes
4answers
387 views

Bias in jury selection?

A friend is representing a client on appeal, after a criminal trial in which it appears that jury selection was racially biased. The jury pool consisted of 30 people, in 4 racial groups. The ...
1
vote
0answers
12 views

$2^3$ Factorial Design conducted in a Latin Square Design

When does the situation occur to conduct a $2^3$ Factorial Design in a Latin Square Design? What would be the procedure of analyzing data of a $2^3$ Factorial Design conducted in a Latin Square ...
0
votes
1answer
63 views

Random and Fixed effect model

Would you explain a practical situation where random effect model is more appropriate than the fixed effect model?
2
votes
1answer
35 views

Comprehensive list of activation functions in neural networks with pros/cons

Are there any reference document(s) that give a comprehensive list of activation functions in neural networks along with their pros/cons (and ideally some pointers to publications where they were ...
3
votes
2answers
80 views

Book for introductory nonparametric econometrics/statistics

My work implies a lot of econometrics, and I had a good formation about it. Nevertheless, I am regularly faced with some semi or non parametric techniques (for instance I had to use quantile ...
1
vote
0answers
64 views

Distribution of correlation coefficients for uniform random variables

Let $n>1$, let $X$ be uniformly distributed on $[-\frac12,\frac12]$, and consider the sequence $X_1,\ldots,X_{n+1}$ of independent copies of $X$. R implements ...
2
votes
3answers
101 views

Beyond the basics: intermediate medical statistics textbooks suggestions

I am a soon-to-be physician. During my studies I have taken a class in biostatistics. I own Martin Bland's "An introduction to medical statistics", which was a required textbooks at the time, and ...
0
votes
0answers
19 views

Big Data Use Cases

I am going to study about big data use cases in the real world. I want the stuff to be preferable in book format(not article or blog posts or website articles) and high level, industry based and ...
6
votes
1answer
120 views

Good papers with reproducible analysis requiring only the basics

I'm looking for papers or other examples of research where the statistical analysis done would be within the grasp of someone who has done an introductory stats course. Ideally the datasets would also ...