Unanswered Questions
50,516 questions with no upvoted or accepted answers
36
votes
2answers
2k views
Probability inequalities
I am looking for some probability inequalities for sums of unbounded random variables. I would really appreciate it if anyone can provide me some thoughts.
My problem is to find an exponential upper ...
29
votes
0answers
1k views
Link Anomaly Detection in Temporal Network
I came across this paper that uses link anomaly detection to predict trending topics, and I found it incredibly intriguing: The paper is "Discovering Emerging Topics in Social Streams via Link Anomaly ...
25
votes
1answer
520 views
Jaynes' $A_p$ distribution
In Jaynes' book "Probability Theory: The Logic of Science", Jaynes has a chapter (Ch 18) entitled "The $A_p$ distribution and rule of succession" in which he introduces the idea of $A_p$ distributions,...
23
votes
0answers
583 views
Bound for Arithmetic Harmonic mean inequality for matrices?
NOTE: This question has originally been posted in MSE, but it did not generate any interest. It was first posted there, because the question itself is a pure matrix-algebra question.
Nevertheless, ...
20
votes
1answer
577 views
Wavelet-domain gaussian processes: what is the covariance?
I've been reading Maraun et al, "Nonstationary Gaussian processes in wavelet domain: Synthesis, estimation, and significant testing" (2007) which defines a class of non-stationary GPs that can be ...
20
votes
0answers
1k views
How to create a multivariate Brownian Bridge
It is known, that a standard multivariate Brownian bridge $ y(\mathbf u) $ is a centered Gaussian process with covariance function
$$ \mathbb E(y(\mathbf u) y(\mathbf v)) = \prod_{j=1}^d (u_j \wedge ...
18
votes
0answers
723 views
How does a Relevance Vector Machine (RVM) work?
Relevance Vector Machines (RVMs) are really interesting models when contrasted with the highly geometrical (and popular) SVMs.
In the light of a question like How does a Support Vector Machine (SVM) ...
18
votes
1answer
414 views
Blind source separation of convex mixture?
Suppose I have $n$ independent sources, $X_1, X_2, ..., X_n$ and I observe $m$ convex mixtures:
\begin{align}
Y_1 &= a_{11}X_1 + a_{12}X_2 + \cdots + a_{1n}X_n\\
...&\\
Y_m &= a_{m1}X_1 + ...
17
votes
1answer
998 views
$ARIMA(p,d,q)+X_t$, Simulation over Forecasting period
I have time series data and I used an $ARIMA(p,d,q)+X_t$ as the model to fit the data. The $X_t$ is an indicator random variable that is either 0 (when I don’t see a rare event) or 1 (when I see the ...
16
votes
0answers
523 views
Fitting custom distributions by MLE
My question relates to fitting custom distributions in R but I feel it has enough of a probability element to remain on CV.
I have an interesting set of data which has the following characteristics:
...
16
votes
0answers
804 views
Diagnostic plot for assessing homogeneity of variance-covariance matrices
Is there a handy plot for comparing the variance-covariance matrices of two (or perhaps more) groups? An alternative to looking at lots of marginal plots, especially in the multivariate Normal case?
16
votes
1answer
681 views
Upper bounds for the copula density?
The Fréchet–Hoeffding upper bound applies to the copula distribution function and it is given by
$$C(u_1,...,u_d)\leq \min\{u_1,..,u_d\}.$$
Is there a similar (in the sense that it depends on the ...
16
votes
0answers
525 views
Distribution of inverse Wishart to a power?
In a related question, I had asked about the norm induced by an inverse Wishart matrix. I am interested in generalizing that result somewhat. Let $A\sim\mathcal{W}_p\left(I,n\right)$, a Wishart matrix ...
16
votes
0answers
890 views
Least stupid way to forecast a short multivariate time series
I need to forecast the following 4 variables for the 29th unit of time. I have roughly 2 years worth of historical data, where 1 and 14 and 27 are all the same period (or time of year). In the end, I ...
15
votes
1answer
308 views
Pooling calibration plots after multiple imputation
I would like advice on pooling the calibration plots/statistics after multiple imputation. In the setting of developing statistical models in order to predict a future event (e.g. using data from ...
