All Questions
207,409
questions
6
votes
4
answers
6k
views
Incorporating boolean data into analysis
I have a data set of about 3,000 field observations.
The data collected is divided into 20 variables (real numbers), 30 boolean variables, and 10 or so look up variables and one "answer" variable
...
- 1,429
56
votes
3
answers
42k
views
Standard deviation of standard deviation
What is an estimator of standard deviation of standard deviation if normality of data can be assumed?
user88
3
votes
1
answer
460
views
Forecasting handbooks
In engineering, we usually have Handbooks that pretty much dictate the state of the practice. These books are usually devoid of theory and focus on the applied methodology. Is there a forecasting ...
67
votes
2
answers
30k
views
What is the difference between a partial likelihood, profile likelihood and marginal likelihood?
I see these terms being used and I keep getting them mixed up. Is there a simple explanation of the differences between them?
- 54.5k
40
votes
11
answers
11k
views
Open Source statistical textbooks?
There have been a few questions about statistical textbooks, such as the question Free statistical textbooks. However, I am looking for textbooks that are Open Source, for example, having an Creative ...
70
votes
8
answers
57k
views
Is PCA followed by a rotation (such as varimax) still PCA?
I have tried to reproduce some research (using PCA) from SPSS in R. In my experience, principal() function from package psych ...
- 3,368
28
votes
1
answer
2k
views
How can one empirically demonstrate in R which cross-validation methods the AIC and BIC are equivalent to?
In a question elsewhere on this site, several answers mentioned that the AIC is equivalent to leave-one-out (LOO) cross-validation and that the BIC is equivalent to K-fold cross validation. Is there ...
- 17.7k
7
votes
2
answers
776
views
Why prediction of a predicted variable from a discriminant analysis is imperfect
I am puzzled by something I found using Linear Discriminant Analysis. Here is the problem - I first ran the Discriminant analysis using 20 or so independent variables to predict 5 segments. Among the ...
- 71
4
votes
2
answers
361
views
Heuristics for optimizing ν-SVM?
Do you know any good heuristics for finding optimal value of ν in case of ν-SVM classification? In this particular problem I have a radial basis kernel, if it helps.
user88
4
votes
2
answers
996
views
Something like E-M for discriminative models?
E-M provides a way to improve the estimation of a generative model with unannotated data. Is there anything out there that works the same way for discriminative models (e.g. perceptrons)?
For example, ...
- 516
18
votes
1
answer
698
views
E-M, is there an intuitive explanation?
The E-M procedure appears, to the uninitiated, as more or less black magic. Estimate parameters of an HMM (for example) using supervised data. Then decode untagged data, using forward-backward to '...
- 516
4
votes
1
answer
375
views
To what extent can we call a Geometric Distribution a Geometric Density [duplicate]
In some papers, for example in "The Geometric Density with Unknown Location Parameter" by Klotz, a Geometric Distribution is called a Geometric Density.
For me, this claim looks erroneous, however ...
- 2,030
21
votes
2
answers
27k
views
What are the differences between the Baum-Welch algorithm and Viterbi training?
I am currently using Viterbi training for an image segmentation problem. I wanted to know what the advantages/disadvantages are of using the Baum-Welch algorithm instead of Viterbi training.
- 501
283
votes
13
answers
236k
views
Is there any reason to prefer the AIC or BIC over the other?
The AIC and BIC are both methods of assessing model fit penalized for the number of estimated parameters. As I understand it, BIC penalizes models more for free parameters than does AIC. Beyond a ...
- 17.7k
20
votes
5
answers
24k
views
Post-hocs for within subjects tests?
What is the preferred method for for conducting post-hocs for within subjects tests? I've seen published work where Tukey's HSD is employed but a review of Keppel and Maxwell & Delaney suggests ...
- 17.7k
11
votes
2
answers
2k
views
How to understand a convolutional deep belief network for audio classification?
In "Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations" by Lee et. al.(PDF) Convolutional DBN's are proposed. Also the method is evaluated for image ...
- 2,030
14
votes
4
answers
1k
views
What graphical techniques are used in Structural Equation Modeling?
I'm curious if there are graphical techniques particular, or more applicable, to structural equation modeling. I guess this could fall into categories for exploratory tools for covariance analysis or ...
- 12.4k
53
votes
4
answers
100k
views
What is difference-in-differences?
Difference in differences has long been popular as a non-experimental tool, especially in economics. Can somebody please provide a clear and non-technical answer to the following questions about ...
- 7,763
44
votes
4
answers
15k
views
What is an instrumental variable?
Instrumental variables are becoming increasingly common in applied economics and statistics. For the uninitiated, can we have some non-technical answers to the following questions:
What is an ...
- 7,763
13
votes
5
answers
6k
views
When to use multiple models for prediction?
This is a fairly general question:
I have typically found that using multiple different models outperforms one model when trying to predict a time series out of sample. Are there any good papers ...
- 12.1k
17
votes
4
answers
1k
views
Comprehensive overview of loss functions?
I am trying to get a global perspective on some of the essential ideas in machine learning, and I was wondering if there is a comprehensive treatment of the different notions of loss (squared, log, ...
- 3,317
103
votes
5
answers
15k
views
Why is ANOVA taught / used as if it is a different research methodology compared to linear regression?
ANOVA is equivalent to linear regression with the use of suitable dummy variables. The conclusions remain the same irrespective of whether you use ANOVA or linear regression.
In light of their ...
user28
9
votes
1
answer
3k
views
How can I use optimal scaling to scale an ordinal categorical variable?
In an answer to this question about treating categorical data as continuous, optimal scaling was mentioned. How does this method work and how is it applied?
- 3,322
64
votes
8
answers
56k
views
Does it ever make sense to treat categorical data as continuous?
In answering this question on discrete and continuous data I glibly asserted that it rarely makes sense to treat categorical data as continuous.
On the face of it that seems self-evident, but ...
- 1,897
104
votes
17
answers
69k
views
Under what conditions does correlation imply causation?
We all know the mantra "correlation does not imply causation" which is drummed into all first year statistics students. There are some nice examples here to illustrate the idea.
But sometimes ...
- 54.5k
12
votes
5
answers
12k
views
What ways are there to show two analytical methods are equivalent?
I have two different analytical methods that can measure the concentration of a particular molecule in a matrix (for instance measure the amount of salt in water)
The two methods are different, and ...
- 1,549
9
votes
2
answers
551
views
Does the cross validation implementation influence its results?
As you know, there are two popular types of cross-validation, K-fold and random subsampling (as described in Wikipedia). Nevertheless, I know that some researchers are making and publishing papers ...
user88
12
votes
3
answers
830
views
Is there a standard technique to debug MCMC programs?
Debugging MCMC programs is notoriously difficult. The difficulty arises because of several issues some of which are:
(a) Cyclic nature of the algorithm
We iteratively draw parameters conditional on ...
user28
29
votes
3
answers
30k
views
Unsupervised, supervised and semi-supervised learning
In the context of machine learning, what is the difference between
unsupervised learning
supervised learning and
semi-supervised learning?
And what are some of the main algorithmic approaches to ...
- 958
31
votes
4
answers
24k
views
What is the best method for checking convergence in MCMC?
What is your preferred method of checking for convergence when using Markov chain Monte Carlo for Bayesian inference, and why?
- 7,763
20
votes
5
answers
685
views
When can you use data-based criteria to specify a regression model?
I've heard that when many regression model specifications (say, in OLS) are considered as possibilities for a dataset, this causes multiple comparison problems and the p-values and confidence ...
- 311
2
votes
5
answers
15k
views
In SAS, how do you copy & paste from the output window?
Sometimes, I just want to do a copy & paste from the output window in SAS. I can highlight text with a mouse-drag, but only SOMETIMES does that get copied to the clipboard. It doesn't matter if I ...
- 2,178
11
votes
6
answers
1k
views
Dubious use of signal processing principles to identify a trend
I am proposing to try and find a trend in some very noisy long term data. The data is basically weekly measurements of something which moved about 5mm over a period of about 8 months. The data is to ...
- 577
30
votes
6
answers
17k
views
Variable selection procedure for binary classification
What are the variable/feature selection that you prefer for binary classification when there are many more variables/feature than observations in the learning set? The aim here is to discuss what is ...
46
votes
5
answers
91k
views
Negative values for AICc (corrected Akaike Information Criterion)
I have calculated AIC and AICc to compare two general linear mixed models; The AICs are positive with model 1 having a lower AIC than model 2. However, the values for AICc are both negative (model 1 ...
- 3,322
57
votes
19
answers
9k
views
Mathematical Statistics Videos
A question previously sought recommendations for textbooks on mathematical statistics
Does anyone know of any good online video lectures on mathematical statistics?
The closest that I've found are:
...
11
votes
3
answers
5k
views
Is it valid to aggregate a time series to make it look more meaningful?
Another question about time series from me.
I have a dataset which gives daily records of violent incidents in a psychiatric hospital over three years. With the help from my previous question I have ...
- 5,633
20
votes
2
answers
4k
views
How does random forest generate the random forest
I am not an expert of random forest but I clearly understand that the key issue with random forest is the (random) tree generation. Can you explain me how the trees are generated? (i.e. What is the ...
- 6,425
9
votes
4
answers
1k
views
Good line color for "threshold" line in a time-series graph?
We're plotting time-series metrics in the context of network/server operations. The data has a 5-minute sample rate, and consists of things like CPU utilization, error rate, etc.
We're adding a ...
- 193
25
votes
6
answers
68k
views
Always Report Robust (White) Standard Errors?
It has been suggested by Angrist and Pischke that Robust (i.e. robust to heteroskedasticity or unequal variances) Standard Errors are reported as a matter of course rather than testing for it. Two ...
- 7,763
377
votes
80
answers
180k
views
What is your favorite "data analysis" cartoon?
Data analysis cartoons can be useful for many reasons: they help communicate; they show that quantitative people have a sense of humor too; they can instigate good teaching moments; and they can help ...
106
votes
32
answers
38k
views
What book would you recommend for non-statistician scientists? [closed]
What book would you recommend for scientists who are not statisticians?
Clear delivery is most appreciated. As well as the explanation of the appropriate techniques and methods for typical tasks: ...
35
votes
4
answers
10k
views
Why isn't RANSAC most widely used in statistics?
Coming from the field of computer vision, I've often used the RANSAC (Random Sample Consensus) method for fitting models to data with lots of outliers.
However, I've never seen it used by ...
- 677
60
votes
6
answers
21k
views
Introduction to statistics for mathematicians
What is a good introduction to statistics for a mathematician who is already well-versed in probability? I have two distinct motivations for asking, which may well lead to different suggestions:
I'd ...
51
votes
6
answers
15k
views
Motivation for Kolmogorov distance between distributions
There are many ways to measure how similar two probability distributions are. Among methods which are popular (in different circles) are:
the Kolmogorov distance: the sup-distance between the ...
- 3,046
3
votes
2
answers
521
views
How to approximate measurement uncertainty?
At the moment I use standard deviation of the mean to estimate uncertainty:
where N is in hundreds and mean is a time series (monthly) mean. I
present it then like this: for each element (month) in ...
- 329
45
votes
16
answers
7k
views
What best practices should I follow when preparing plots?
I usually make my own idiosyncratic choices when preparing plots. However, I wonder if there are any best practices for generating plots.
Note: Rob's comment to an answer to this question is very ...
5
votes
2
answers
230
views
How to tell if something happened in a data set which monitors a value over time
I have a data set where a series of measurements are being taken each week. In general the data set shows a +/- 1mm change each week with a mean measurement staying at about 0mm. In plotting the data ...
- 577
7
votes
0
answers
492
views
Testing (and proving) the randomness of numbers [duplicate]
Possible Duplicate:
Testing random variate generation algorithms
What's a good way to test a series of numbers to see if they're random (or at least psuedo-random)? Is there a good statistical ...
- 755
9
votes
1
answer
2k
views
What are pivot tables, and how can they be helpful in analyzing data?
What are pivot tables, and how can they be helpful in analyzing data?
- 755