"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
51 views

Intro Stat Text for Rigorous 3-week Course?

I will be teaching an introductory statistics course to gifted middle-school students over the course 3ish weeks. I'll have about 90 contact hours with the students. Any recommendations on a concise ...
1
vote
0answers
19 views

Textbooks on stochastic calculus and stochastic differential equations

I am looking for key reference books in stochastic calculus, Stochastic Differential Equations (SDEs) as well as Stochastic Partial Differential Equations (SPDEs), from the most theoretical to the ...
0
votes
0answers
7 views

Relationships among different definitions of Sobolev spaces

In Tsybakov's book(Page 51), Sobolev space (or Ellipsoid) for positive smoothness parameter $s$ is defined with sequential model, i.e. the series of the Fourier coefficients is finite. On the other ...
0
votes
0answers
13 views

Reference on interpretation of similar observed values and average adjusted predictions

I analyzed the association between a count dependent variable (DV) and a dummy independent variable (IV) (coded 0 and 1) ...
5
votes
0answers
34 views

Does using bootstrapped samples improve parameter estimates for a fitted distribution?

The R package retimes has a function for fitting an ex-Gaussian distribution to a set of observations. The method involves taking multiple bootstrapped samples of the observations, and fitting the ...
0
votes
2answers
52 views

Best classical statistics books

This question has been asked many times before but I didnt find great references - so here's another try :) I am looking for basic statistics book that would be of the level of advanced undergrad. ...
-1
votes
0answers
20 views

Tutorials on main machine learning algorithms [closed]

I was asked during an interview to give my favourite machine learning algorithm and describe it. For different famous algorithms (like decision trees, svms etc), which paper would you suggest to ...
2
votes
0answers
29 views

parameter and prediction confidence intervals

We have a correctly specified linear model $z = x\beta + \varepsilon$ with 100 independent observations. Given: $y = e^z$, $\sigma^2 = 4$ (assumed to be known), sample means $\bar{x} = -3$ and ...
0
votes
0answers
15 views

Test if 2 samples are taken from the same population (multi-dimensional data) - worked example

I'm looking to learn (not just apply) how to test is two samples are drawn from a single population. The data I'm likely to apply this to is multi-dimensional so that's my target. Can anyone give me a ...
1
vote
1answer
40 views

reference case-control sampling

I have to use a case-control sampling design to apply logistic regression. I'm looking for a reference that explains which are the advantages and disadvantages of using a high case-control ratio ...
2
votes
1answer
58 views

Best graduate level text for econometric time series?

I am a masters student studying economics. The program that I am attending is extremely quantitative with a heavy focus on econometrics. I am looking for a text on time series analysis. I really ...
4
votes
0answers
35 views

Review paper on particle filter

I have found online a draft of an excellent review paper by Zhe Chen entitled "Bayesian Filtering: From Kalman Filters to Particle Filters, and Beyond". According to Google Scholar, the citation for ...
4
votes
2answers
79 views

Statistical analysis in the cryptoanalysis of the Enigma cipher machine (safeguarding of the intelligence source in Ultra)

During the second world war the British were doing cryptanalysis of the German Enigma cipher machine and subsequent signals intelligence. One of the issue was about the safeguarding of the source of ...
1
vote
0answers
7 views

Separability measures

I am just studying pattern recognition. In that regard, my question is Why we need separability measures? Would you please give me detail explanation and suggest some books to read?
6
votes
7answers
750 views

Why not validate on the entire training set?

We have a dataset with 10,000 manually labeled instances, and a classifier that was trained on all of this data. The classifier was then evaluated on ALL of this data to obtain a 95% success rate. ...
3
votes
2answers
94 views

How can I measure fluctuation?

For a certain product I have a data series with its price for each day over a long period of time (20 years). I want to investigate how the fluctuation of the price changes over the whole time. ...
2
votes
3answers
48 views

A good intro to computational linguistics?

I have a pretty good background in data analysis and statistics in the social sciences, including both frequentist and Bayesian paradigms, and I have recently been introduced to computational ...
9
votes
5answers
262 views

Textbook for Bayesian econometrics

I am looking for a theoretically rigorous textbook on Bayesian econometrics, assuming a solid understanding of frequentist econometrics. I would like to suggest one work per answer, so that ...
1
vote
5answers
156 views

Thoughts on Mathematics of Statistics by Kenney? [closed]

This book is written in 1939. It's available here on archive.org. Would you recommend this as an introduction to the mathematics of statistics for beginners?
5
votes
3answers
78 views

Textbook on reinforcement learning

I am looking for a textbook/lecture notes in reinforcement learning. I'm fond of the "Introduction to Statistical Learning", but unfortunately they do not cover this topic. I know that a book by ...
-1
votes
2answers
55 views

Social Science Trade Book

I am looking for a book (not textbook) to use in an undergraduate statistics course. I would like to find a book with a clear central thesis relying largely on statistical reasoning and evidence to ...
0
votes
1answer
60 views

Resources for learning R with Statistics [duplicate]

Already read: Resources for learning R I would prefer to have a textbook which covers statistics with R, accessible to a beginning graduate student in statistics. Since I'm not as familiar with R as ...
2
votes
1answer
46 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
26 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
299 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
59 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
81 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
20 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
178 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
58 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
735 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
33 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
31 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
16 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
49 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
26 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
59 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
143 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 ...
11
votes
3answers
946 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
17 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
52 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
40 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 ...