"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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References for visually inspecting underlying model assumptions

In connection to this popular question in CV, I was wondering which peer-reviewed papers / books could be used as references about using visual inspection of q-q plots etc. as compared to performing ...
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0answers
6 views

Help in state and parameter estimation when a time series model excited by pseudo binary input

An IIR system is excited by a pseudorandom binary signal $z_n$. The output of the system is corrupted by zero mean additive white Gaussian noise and this is observed, i.e., $y_n = \mathbf{h^Ty_{n-1}} ...
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0answers
7 views

A good read to recommend on stochastic processes?

can you recommend a good read, ideally up-to-date, for stochastic processes? I am not afraid of math, all I appreciate is the fluency of materials. I've read about Dirichlet/Pitman-Yor/Gaussian ...
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1answer
71 views

Mathematical Modeling and Statistical Modeling

What is the difference between mathematical modeling and statistical modeling? I only know that a mathematical model is deterministic while a statistical model is stochastic. Is that all to answer ...
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22 views

Who to credit for “control functions” in econometrics?

The idea is pretty simple, and I think it came out sort of by-the-way in a paper about something else, so I'm having a hard time figuring out who to cite. Basically you've got a GLM (like a probit or ...
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0answers
34 views

Huber's M estimator for contaminated Gaussian noise

Huber discussed in this seminal paper "Robust Estimation of a Location Parameter" link that if we have some observations $x_i$ as follows: $$y_i = \theta + \nu_i, ~~i=1,\cdots,N, \tag{1}$$ where ...
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0answers
7 views

References regarding correlations with ranks and binary data

I have several rank variables (ranks 0-3), which can be reasonably turned into binary (significant/insignificant effect). I'm looking for potential interactions. What would be the best source to look ...
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0answers
21 views

Question about Statistics resources [closed]

Does anyone have a good resource for studying statistics? Specifically chapter 9 of tps3e by Yates, Starnes, and Moore? Or sample distributions and means?
1
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1answer
75 views

What inputs, ideas or insight the community can offer on the subject “A simulation study of sample size for multilevel logistic regression.” [closed]

I have been assigned a topic on "A simulation study of sample size for multilevel logistic regression." I have searched the topic but found little reference on it. Could you please offer some ...
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0answers
16 views

On Kolmogorov's Theorem In Time series theory and methods (1990)

I am following Time series theory and methods, Brokwell and Davis (1990). And theorem 1.2.1 called by the text Kolmogorov's Theorem is only stated but not proven. I will rewrite it here: The ...
0
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0answers
8 views

Online Resources for Evolution of Statistical Methods in Different Disciplines

From time to time I like to read something about how data is analyzed in different disciplines. I think it is interesting to see what statistical methods are applied in different areas. Especially ...
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4answers
1k views

What is a good book about the philosophy behind Bayesian thinking?

What is a good book about Bayesian philosophy, contrasting subjectivists against objectivists, explaining the view of probability as state of knowledge in Bayesian statistics, etc.? Maybe Savage's ...
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0answers
8 views

Acceptance Sampling Plan

I was reading Acceptance Sampling Plan but didn't understood when should I use single sampling plan , when double sampling plan , when multiple sampling plan and when sequential sampling plan. Also ...
2
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1answer
24 views

Parameters in a non-parametric model

I have not understood this Wikipedia statement: The difference between parametric model and non-parametric model is that the former has a fixed number of parameters, while the latter grows the ...
3
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0answers
56 views

Need pointers to deep learning tutorials

I'm looking for good study material about deep belief networks, with particular emphasis to classification and feature extraction tasks for non-image data. I don't seem to find a great deal about ...
0
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0answers
10 views

Introduction to degradation models

Could you please give me some introductory reference to Degradation Models? I took a look at the reliawiki link but it is too short and contains no references at all.
2
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1answer
36 views

Example-driven book recommendation for learning statistics

I have always found learning statistics to be hard without seeing examples, and taking for granted the answer. I am looking for a book that teaches statistics that fits my criteria below or comes ...
0
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1answer
33 views

Difference between “Design based approach” and “Model based approach”?

In a pdf file, i found the following thing which i have not understood at all. ‐ one view (e.g., Heckman, 2008): causality is model‐based: causality only exists within the framework of a theory ...
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0answers
19 views

Model and Modeling

model and modeling seem identical to me. Aren't those really same ? (or is there any flaws so that they are two different tags.) And in model tag, it is written ...
2
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0answers
17 views

Do mildly informative prior distributions tend to mitigate false positives (i.e. Type I error rates)?

I am curious if others have sources that speak to the matter that providing informative and/or mildly informative prior distributions on a parameter tend to mitigate false alarm rates? I know from the ...
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1answer
23 views

Are sensitivity and specificity complement of each other?

Sensitivity : probability that a person with the condition will be classified in one's study as having the condition. ...
1
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0answers
33 views

What is industrial statistics?

We have a course titled "Industrial Statistics". But I don't understand what is industrial statistics? What I have understood after searching some sites is only that Industrial statistics ...
1
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1answer
25 views

transform of predictor variables

Assume I have a linear model like this: $$ y_i = \beta_1 x_{i1} + \cdots + \beta_{ip} x_{ip} + \varepsilon_i \hspace{1cm} i = 1,\dots,n $$ I know that if $y_i$ must be greater than zero, I should ...
0
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0answers
49 views

why can't I use random sampling in logistic regression when classes are unbalanced?

I don't understand why in a logistic regression model if we have lots of y=0 and few y=1 in the population and I use classical logistic regression (so the classical maximum likelihood estimator), then ...
0
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0answers
19 views

How to estimate density of multi dimensional data

Doubts are based on MLE of intrinsic dimension by E. Levina. Please correct me where wrong. The Authors propose ML estimator for the dimension $m$ using the nearest neighborhood distance information. ...
0
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0answers
21 views

References on analysis of outliers

I need some advice on literature, preferably papers, that explain the basics of outlier analysis. Does anyone have any tips?
1
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0answers
19 views

Who first suggested to approximate phases from a time series via marker events?

A rather simple approach to approximating an instantaneous (unwrapped) phase $φ$ from a time series is as follows: Define some a appropriate marker events (e.g., upwards zero crossings) $t_0 < … ...
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2answers
1k views

Why are “time series” called such?

Why are “time series” called such? Series means sum of a sequence. Why is it time Series, not time sequence? Is time the independent variable?
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0answers
46 views

Nate Silver's Election Prediction Model

Nate Silver has been quite successful at predicting the outcomes of U.S. elections in the past, something which is described in his book The Signal and the Noise. The book contains some descriptions ...
0
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1answer
36 views

Is Randomized Complete Block Design a two-way anova?

Isn't Randomized Complete Block Design a two-way anova ? Can it be one-way ? As far i understand, since there is treatment effect and also block effect in RCBD, it is two-way anova. But can it be ...
0
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0answers
14 views

Is there a framework for dealing with time-varying sequences of matrices (specifically for applications to finance, involving PCA)?

I am using principal component analysis to model yield curves for certain financial instruments. My dataset is a matrix $X$ where $[X]_{ti}$ is the observation of the $i$th instrument on day $t$. I am ...
4
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1answer
43 views

Linear transformation of a random variable by a tall rectangular matrix

Let's say we have a random vector $\vec{X} \in \mathbb{R}^n$, drawn from a distribution with probability density function $f_\vec{X}(\vec{x})$. If we linearly transform it by a full-rank $n \times n$ ...
2
votes
1answer
61 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 ...
0
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0answers
27 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
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0answers
18 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) ...
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0answers
42 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
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2answers
73 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. ...
2
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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
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0answers
21 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
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1answer
44 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
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1answer
73 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
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0answers
42 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
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2answers
143 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 ...
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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?
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7answers
780 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
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2answers
117 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. ...
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3answers
52 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
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5answers
279 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
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5answers
162 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
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3answers
87 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 ...