Questions tagged [probabilistic-forecasts]

The tag has no usage guidance.

Filter by
Sorted by
Tagged with
2 votes
1 answer
53 views

Backtransforming a probabilistic forecast?

Let's say that we have a probabilistic forecast for the future percentage return of an asset in the form of a probability density, $\hat{R}_{t+1}$. If our initial goal was to create a probabilistic ...
QMath's user avatar
  • 389
0 votes
0 answers
13 views

Triplets, Sampling Criteria and Variance?

Say I have a population size of 1000 students from schools in different towns (assume they are in the same class year, of mixed gender, same country/state). The mean, variance and standard deviation ...
Danny Yatch's user avatar
0 votes
0 answers
36 views

Resources for Probabilstic forecasting

I was planning on learning probabilistic forecasting and im completely lost. Suggest some online resources. I have started with Probabilistic Forecasting and Bayesian Data Assimilation but its a bit ...
cosm1c v1bes's user avatar
1 vote
0 answers
61 views

Is there a closed form for multi-step ARIMA/ARMA density forecasts conditioned on initial values?/alternatives to this?

I am attempting to create a benchmark for probabilistic forecasting of time series to test other models against and figured that a linear ARIMA/ARMA model would be a good starting point. I thought ...
QMath's user avatar
  • 389
1 vote
0 answers
43 views

Is generation/evaluation of probabilistic predictions on continuous data feasible for larger data sets in practice?

To better capture uncertainty about the phenomena that we model, probabilistic predictions seem to be a natural and common extension of point predictions. Methods for evaluation of these predictions ...
QMath's user avatar
  • 389
0 votes
0 answers
17 views

The dependency in the instances of a random variable [duplicate]

Suppose we have a list L of all root words in English numbered from 1 to n. The data is any English text (let's say a text from a book) where each word is replaced by its root. You are given the data ...
Mosab Shaheen's user avatar
1 vote
0 answers
46 views

Do "types" of predictions "need" to match assumptions about data?

Let $\mathcal X$ (observation space) and $\mathcal P$ (prediction space) be non-empty sets. Let $P$ be a variadic function (predictive model) mapping tuples of elements of $\mathcal X$ into $\mathcal ...
QMath's user avatar
  • 389
1 vote
0 answers
15 views

Problem formulation of future timeframe prediction based on current time

I have a problem where I want to predict "when is the next action happening" based on the time. Example problem: Imagine you have a dataset of transactions per user, your goal is to predict ...
xdaniel's user avatar
  • 31
2 votes
0 answers
225 views

How to assess calibration of probability distribution for a multiclass model?

I have a multiclass classifier (boosting model), and my goal is to have a good approximation of the actual distribution to the classes given my feature values. I.e. suppose I have features $X$, and ...
Lys's user avatar
  • 56
2 votes
1 answer
40 views

Should Bayesian probability of model given the data coincide with intuitive estimation of this probability?

I have $N$ real valued targets ordered by one single real valued feature. I would like to build a simple probabilistic model that states that all the targets corresponding to the features that are ...
Roman's user avatar
  • 584
0 votes
1 answer
100 views

Scale-Invariant CRPS Alternative

I am currently working on a probabilistic forecasting problem (outputting the full predictive distribution, possibly in the form of samples) and I need to decide on a measure to evaluate the forecasts....
Filippo Fedeli's user avatar
1 vote
0 answers
143 views

How can I generate probabilistic forecasts to do probabilistic classification?

I have a collection of univariate, irregularly spaced, financial time series. Each series is labeled by its class. The image below shows some example data. A note on the data: The time series could ...
Escherichia's user avatar
2 votes
0 answers
122 views

One-vs-rest vs one-vs-one multiclass probability validation: does it matter?

Now that I have figured out how rms::val.prob works to the extent that I have written my own Python implementation, I would like to extend that idea to multiple ...
Dave's user avatar
  • 62.5k
1 vote
2 answers
162 views

Predictive distribution in the Frequentist setting

Let $\{X_t\}_{t \in T}$ be a time series, such that $X \sim F(\theta)$, for some arbitrary distribution $F$. Based on the observed values $\{x_1, x_2, \cdots, x_{t-1}\}$, suppose that I want to ...
bbublue's user avatar
  • 37
1 vote
3 answers
106 views

How to combine state-level COVID-19 vaccination rates with national demographic data at the individual level?

I’m investigating possible correlations between the COVID-19 vaccination rate in the United States and the results of a long-running survey of scientific personality traits like "Agreeableness&...
Chris Wilson's user avatar
0 votes
0 answers
106 views

Computing probabilistic forecasts for a ratio of two other given forecasts

I have three time series (Revenue, Volume and Price), with Price = Revenue / Volume. I have created probabilistic forecasts for Revenue and Volume and now need to derive a consistent forecast (...
stats-hb's user avatar
  • 289
3 votes
1 answer
194 views

Nonlinear regression: What's the best estimator for this problem?

Context and goals: Consider $x$ a scalar (deterministic) independent variable and $y = f(x;\beta)+\eta$ be a dependent random variable obtained trough $f$ with some parameters $\beta$ and $\eta$ is ...
FeedbackLooper's user avatar
0 votes
0 answers
112 views

Which algorithm suits for classification of multivariate time series data?

I have multivariate time series data, where the goal is to predict a binary label, which is changing in time. For illustration: there are 20 individuals, for each of them I measure 50 values (...
pikachu's user avatar
  • 753
2 votes
0 answers
370 views

What method would I use when data has an upper and lower boundary in GluonTS

I have a time series dataset that has a max ceiling of 50 and a lower threshold of 0, however when using probabilistic time series modeling like GluonTS I am getting future predictions that are either ...
G Gr's user avatar
  • 1,011
2 votes
1 answer
31 views

Distribution that acts like Poisson/NegBin for small means and like a Normal distribution for large means?

I want to generate a full density probabilistic forecasting model, where I don't know a priori whether the time series I want to model are intermittent or dense. In both cases, the time series is a ...
Akaike's Children's user avatar