Tagged Questions

0
votes
0answers
11 views

Mean absolute percentage error (MAPE) in Scikit-learn

How can we calculate the Mean absolute percentage error (MAPE) of our predictions using Python and scikit-learn? From the docs, we have only these 4 metric functions for Regressions: ...
0
votes
0answers
52 views

Statistical tests on the revenue data of a small business

I have daily revenue data from a small business with 6 locations. The business sells food products that range from roughly \$2.00 to \$9.00, mainly to professionals. They do over a million dollars a ...
2
votes
0answers
19 views

Predict binary occupancy vector from history of vectors

I have a set of binary vectors where each vector represents one day of occupancy in a house and consists of 48 elements (each element for 30 minutes of the day). Each element can be 1 meaning that ...
0
votes
1answer
45 views

Simulated single value based on multiple chains in RJAGS

I am using RJAGS to simulate the posterior distribution of event that a certain candidate will win the presidential election. I need to find the actual percentage that one of the candidates will have. ...
1
vote
1answer
82 views

Time series prediction when data is not i.i.d

I have time series data $y_t$ with covariates $x_{1,t}, x_{2,t}, ...$. The covariates represent budgets for different programs. I can create an ARIMAX model that fits the data very well so far. In ...
3
votes
2answers
85 views

Licenses renewals prediction

I have come recently to the following real world problem concerning licence renewals of a software product. I have just rudimentary knowledge of the basics in this field and I mostly interested in ...
0
votes
3answers
183 views

Regression model for predicting sales?

We sell machinery. The following is graph is an approximation of units sold over time for a particular piece of equipment1 : It starts out slow and slowly grows over time. I tried using linear ...
3
votes
1answer
55 views

Route to understanding and implementing statistical timing models

The research paper Forecasting NBA Player Performance by Douglas Hwang describes a method for predicting player performance by utilizing a statistical timing model and a 'Weibull-Gamma' distribution. ...
0
votes
1answer
43 views

How do you choose the timeframe for a prediction to be tested?

To (hopefully) clarify the question a bit more if you have a broad working hypothesis that x influences y, on a causal/predictive basis (e.g. if x goes up in time t, then you would expect y to go up ...
2
votes
0answers
204 views

Implication / Interpretation of long term equilibrium VECM

I want to test the influence of exchange rates on a price index and struggle with the interpretations. My variables are I(1) First, I ran an OLS on first differenced variables which indicated a ...
0
votes
1answer
322 views

What are the problems with small sample size based predictions when using time-series data?

I had to put the majority of the question in the textbox as Cross Validated didn't like the fact my question was too long....but here it is, in terms of what I wanted to ask: Due to a small sample ...
4
votes
2answers
219 views

Can survival analysis be used to predict earthquakes?

Given survival analysis relates to an analysis/prediction of time to an event, I was wondering if it was possible to be used to predict eathquakes. If so, how would one go about carrying out that ...
2
votes
0answers
128 views

Support vector machines and Granger causality

I was wondering if Granger causality would be an efficient tool for searching for relevant input data for an SVM system. For example if I want to forecast SP 500 returns, I could put in my input data ...
6
votes
0answers
156 views

Finding the correct data mining approach

(I apologise for being a newb, but I'm a researcher introducing myself to data mining---any help or insight would be greatly appreciated. Also, this isn't technically a homework question, but I've ...
1
vote
2answers
90 views

How to model stocks of a warehouse time series?

Warehouse buys products from producer irregularly in bulk quantities. If the warehouse buys a lot of product units at one time the warehouse stops buying for several weeks (let's say week is a time ...
1
vote
1answer
55 views

Time intervals for modeling

Suppose we have weekly data for some attribute (e.g. housing prices). Say that we have $500$ weeks worth of housing price data. Suppose some major event happened on week $256$. If we want to detect ...
1
vote
0answers
133 views

Gaussian process - dimensionality reduction

Specific question on Gaussian Processes and dimensionality reduction. I saw a a method for dimensionality reduction for the squared exponential covariance function (not ARD) whereby one uses a GxD ...
-10
votes
1answer
460 views

Finding the best two predictor variables used conjointly, and levels of each

Twenty possible predictor variables in data set. One outcome variable. Some of the predictor variables are not linear. So a standard linear multiple regression approach probably won't do. (And I ...
1
vote
1answer
117 views

Characterizing the inter-arrival time of software threads

For a multi-threaded application, I want to identify the nature of the application based on the arrival times of each thread. Example(Are thread launch spaced regularly, are they bursty in nature or ...
2
votes
0answers
69 views

Cyclostationary time series

http://en.wikipedia.org/wiki/Cyclostationary_process What are the methods in modelling and forecasting such time series? It is mentioned in the link above that there is a deterministic approach to ...
1
vote
0answers
122 views

SVM and non-linear predictive models - feature selection

Just throwing out a general question. What do people think of applying feature selection methods when using SVMs to build predictive models? I understand that SVM have built in regularization with how ...
3
votes
2answers
450 views

Pre-processing time series data for data mining / predictive modeling input

What are some ways to prepare/pre-process time series data to use the series data as a predictor(s) in a predictive model (classification or regression)? Specifically, what are the methods to be ...
1
vote
4answers
376 views

What method is suitable for short-term forecast for a trendless, oscillatory, bounded time series?

I am new to time series analysis and I would appreciate if anyone could provide me some insight on it. I am trying to analyse a past series of numbers that fluctuates between 107 & 210 with a ...
1
vote
1answer
182 views

Test for accuracy of prediction of financial time series

I would like to test a proprietary method of financial time series prediction that says, in effect, that on a certain day/week in the future, to an accuracy of +/- 2 to 3 days/weeks, a financial time ...
0
votes
1answer
127 views

High dimensional time series

I'm not sure what words I should look for. I have an under determined dataset of 8000 correlated variables (sales) over 12 months (ie 12 observations for each variable). And I basically want to ...
1
vote
1answer
120 views

Algorithms for predicting a couple points in the future

I'm familiar with supervised learning algorithms like regression and neural networks which look at a bunch of input points and learn a function which outputs a value (the value varying depending on ...
3
votes
0answers
71 views

Confidence intervals for difference in time series

I have a stochastic model used to simulate time series of some process. I am interested in the effect of changing one parameter to a specific value and want to show the difference between the time ...
6
votes
1answer
277 views

How can I generate predictions from the randomSurvivalForest package in R?

I'm trying to use the randomSurvivalForest package in R to predict the next event in a series of events (using ...
7
votes
2answers
396 views

Machine learning techniques for time series estimation - forecasting price

Can anyone recommend any machine learning techniques for time series estimation? I have a series of times $t_{1}...t_{n}$, each having a set of associated features $f_{1}...f_{m}$, and a value $x$. ...
2
votes
2answers
159 views

How can you predict the likelihood of someone doing something given previous data?

I'm having a hard time explaining this (hence the weird and long title), also I'm not a mathematician, I have this data lying around in a database and was wondering how I could visualise it (and ...
5
votes
2answers
153 views

Time series factor model with one series more frequent

Let's say I have two time series, one of which updates more frequently than the other: $x_0,x_1,x_2,\dots,x_t,\dots$ $y_0,y_{10},y_{20},\dots,y_{10t},\dots$ I want to fit a model to this that ...
6
votes
2answers
162 views

Estimating event probability from historical time series with clear seasonality

I would like to predict the average number of days in a year for which two conditions are true: daily average temperature is below zero celsius the day was preceded by at least four days with daily ...
6
votes
2answers
68 views

Weighted discrete measurements of a value changing over time

The best way I can think to describe this question is by example: Imagine there is a ship sailing around the pacific ocean on an unknown path (possibly random.) Other ships passing by sometimes see ...
4
votes
4answers
368 views

Combining 2 sets of coefficients, weighting one of the sets

I have two sets of coefficients from similar data taken at different times. What I want to do is combine the two sets of coefficients giving greater weight to the more most recent set. The goal is ...
7
votes
2answers
194 views

General approaches to model car traffic in a parking garage

a friend of mine has asked me to help him with predictive modelling of car traffic in a medium sized parking garage. The garage has its busy and easy days, its peak hours, dead hours opening hours (it ...
9
votes
1answer
373 views

Predicting long-memory processes

I'm working with a two-state process with $x_t$ in $\{1, -1\}$ for $t = 1, 2, \ldots$ The autocorrelation function is indicative of a process with long-memory, i.e. it displays a power law decay with ...
5
votes
3answers
1k views

Predicting from a simple linear model with lags in R

I have a dataset that I want to fit a simple linear model to, but I want to include the lag of the dependent variable as one of the regressors. Then I want to predict future values of this time series ...
7
votes
2answers
1k views

Predicting daily electricity load - fitting time series

I want to predict inter-day electricity load. My data are electricity loads for 11 months, sampled in 30 minute intervals. I also got the weather-specific data from a meteorological station ...
5
votes
1answer
109 views

Predicting a semi-deterministic process

Say I have a process that gives me 3 outputs: $O^1$, $O^2$ and $O^3$. The outputs are generated from a semi-deterministic process, i.e. there is a deterministic component in the outputs, along with a ...