0
votes
0answers
31 views

Forecasting agricultural commodity prices with R

I would like to create a predictive model in order to forecast the price of an agricultural raw material. I got time series for the prices and the production of this raw material, and also for the ...
0
votes
0answers
41 views

temperature prediction algorithm

I found an interesting problem in a contest on temperature prediction: https://www.hackerrank.com/contests/expansion-challenge/challenges/temperature-predictions It is not about forecasting the ...
2
votes
2answers
53 views

Forecasting: Different Model for 1 month, 2 month, 6 month forecasts?

I'm still trying to expand my statistics and forecasting technique knowledge. Right now I'm forecasting seasonal contact patterns, so the simplest model I can understand with seasonality is a ...
1
vote
1answer
30 views

spatial-location/time-series prediction models

How efficient it is to build predictive model. However, every crime is dependent on three factors: Time, Spatial Location and people behavior. Statistically, we can't measure people behavior (we ...
1
vote
1answer
29 views

Individual slopes for many zip codes over time

I have a dataset where I am interested in calculating a slope for each observation / row. I have dependent variable $Y$ that is continuous. Every $Y$ is unique to a zipcode. and my independent / ...
2
votes
1answer
84 views

Logistic regression with time series predictor data

I like to know if we can model binary outcome with time series predictors. For example lets say Y is binary. $X_1, X_2, X_3,...,X_n$ is the same predictor variable but is a historical snapshot over ...
1
vote
1answer
59 views

Increasing the accuracy of tbats() forecasts by factoring for correlations between different time-series?

This question builds on my previous question Forecasting Hourly Time Series based on previous weeks and same period in previous year/s. My project is to forecast the number of ~400 different types of ...
1
vote
0answers
88 views

Forecasting Hourly Time Series based on previous weeks and same period in previous year/s

The Problem I have been tasked with a similar problem to that described in Forecasting hourly time series with daily, weekly & annual periodicity. My data shows the number of times that one of ...
0
votes
0answers
89 views

Binomial GLM - Predicting the time of buying of a product

I'm trying to predict the frequency of buying a product based on data I have. I have two things to consider: 1- Predicting the success of buying this product based on frequencies (0: Failed ; >0: ...
0
votes
0answers
55 views

How to predict when the next event occurs, with random data

I am working on an academic project, I'd like to know what is the best approach to build a predictive model to predict when the next event occurs. I am working on predicting a specific kind of ...
0
votes
0answers
27 views

Are trend/cycle filters intended to be used in predictive models, or just analysis?

I am relatively new to time series modelling and for a task I have I've had good success (in terms of forecast error) by first splitting the data into a trend and cycle components using a ...
1
vote
0answers
44 views

Neural net model - error during training

I'm getting started with R, I really like it but recently I found myself in a corner. I'd like to build neural network model that predicts heat consumption. I have historical data that contains ...
0
votes
0answers
29 views

Literature for prediction models where each training example has a different amount of data?

This could be a machine learning question as much as a statistics question, but I think this is the best place to put the question. Here are three different examples of problems where each ...
0
votes
0answers
32 views

How to model to improve the room usage efficiency based on motion sensor history

To reduce the confusion, I changed my application from traffic to meeting room, so this application is about modeling a meeting room efficiency , the data collection is built by placing a kind of ...
1
vote
1answer
115 views

Suggest models for prediction based on small sample data

I am not a traditional statistics guy. I am from an electrical engineering background. So, spare me for lack of jargon. The model is to be used for predicting agricultural output based on previous ...
0
votes
0answers
21 views

Which method(s) for forecasting time series of event durations

I have the $N$ individuals each observed for $T$ days. For each individual I have some basic demographic data. Each $n$ individual, during the observed time $T_n$ may experience event $E$ which is ...
1
vote
0answers
80 views

ARIMAX for modelling daily sales

I am trying to model daily sales for a take out restaurant. They are only open on business days - no holidays or weekends - as their primary clients are office workers on their lunch breaks. Below is ...
0
votes
2answers
40 views

Time Series Forecasting Method to use both Predicted and Predictor variables

I am learning Predictive modeling and building a Forecasting model to predict Insurance sales in US as a part of my academic project. I want to do Time Series forecasting. I have Y(t) as my response ...
4
votes
1answer
159 views

Time series prediction: visualising path uncertainty region

I am predicting a time series' future evolution and am evaluating the path uncertainty using bootstrapping. Is there a good way to visualise the uncertainty that goes beyond simply plotting a pair of ...
0
votes
0answers
45 views

Data mining of time series

I have a dataset which consist of n time series variables $X_1$..$X_n$ , and a time serie output $Y$. I would like to mine the data to find if some functions (lagged or not) of the $X_i$ can predict ...
0
votes
0answers
38 views

Financial Time series prediction/ SV Regression

I'm working with R software (Lib e1071) and I'm trying to get predictions using Support Vector Regression. The way I'm doing it is the following: I'm windowizing the raw closing prices using N=3 ...
0
votes
0answers
59 views

Time Period Predictive Modeling

I have been implementing some classification algorithms (Naive Bayes, SVM etc) recently on the iris data sets to get head start into the data science field. I enjoy working on machine learning ...
3
votes
1answer
84 views

Predicting a continuous outcome using point process descriptors

I have measured a series of times for discrete events along with a continuous variable. So essentially I measure a point process $P: t_1, t_2, \dots, t_n$ and values $A_1(t=x_1), A_2(t=x_2), \dots, ...
0
votes
1answer
94 views

Principles of Time Series Clustering

I would like to understand complexity of time series clustering. Clustering is similarity based, so as a basic step we evaluate distance between to points in a multidimensional space. In time series, ...
8
votes
2answers
143 views

Coupling time series information from sources with multiple spatial resolutions/scales

I have many satellite raster images available from different sensors. From these, the coarser ones have a very abundant temporal resolution. The medium resolution rasters tend to have less acquisition ...
2
votes
0answers
41 views

Train timeseries model in R and predict purely on out-of-sample data

I have two data files "train.txt' and 'test.txt' with single columns of data. I want to learn a model only on training-data and generate an output on test-data. I can't seem to find a way to do that. ...
2
votes
0answers
59 views

rain cloud radar image prediction

I have a small pet project, which evolves around predicting a radar image of rain clouds given past radar images... My data comes from the radar images on following site: ...
2
votes
2answers
149 views

Best way to visualize predictions from a linear model

Let's say I'm doing some predictive analytics and am trying to predict US GDP per month using a two or three month lag. After every month, I generate new predictions and am able to compare my ...
0
votes
1answer
56 views

How can I find out how shifts in a country's fiscal policies affect its economic health?

I have the values of certain variables for 20 years for different countries... I am unable to understand how to use the values of a particular variable for 20 years. Could anyone suggest how I should ...
1
vote
1answer
166 views

Auto-Regressional & Moving Average Model Formula Properties

I seeking help in understanding specific values underlying the formula's for the MA(p) model & the AR(q) model. I am attempting to implement the models (building up to the combined ARIMA model) in ...
1
vote
3answers
153 views

What model should one use for this short time series?

Below I have quarterly total sales on the left (dependent variable), and a sample of the sales on the right. The two variables share a correlation of 98.7%. What model should I use to predict X? ...
0
votes
0answers
48 views

Building models with unequal intervals between time series observations

I'm trying to get into econometric/trading modeling and the universe of variables out there is immense. There are practically continuously updated variables (currency exchange rates, interest rates, ...
1
vote
1answer
229 views

Building a forecast model based on past year data in R

I am attempting to build a model to forecast attendance in a given week in the current year based on this year's attendance values up until the present, and data from two previous years. My data looks ...
2
votes
0answers
132 views

Forecasting time-series ahead by multiple time horizons

Suppose that I have daily data on the population of a small village, given by $Y(t)$, as well as daily data on various factors that are relevant to the size of the population in the future, given by ...
2
votes
1answer
450 views

Hidden Markov model for event prediction

Question: Is the set-up below a sensible implementation of a Hidden Markov model? I have a data set of 108,000 observations (taken over the course of 100 days) and ...
0
votes
1answer
125 views

Practically handling many non-stationary forecasting predictors

This question is about specific strategies to deal with non-stationary variables in forecasting. This problem usually rears its ugly head when you have a predictor whose levels are relevant to the ...
2
votes
2answers
185 views

Variable selection in time-series forecasting

I have a time-series forecasting task and would like some input on variable selection and regularisation. My problem has the following characteristics: 2,000,000 sample size. Most of the time, no ...
3
votes
0answers
89 views

Predicting for month in R

I'm trying to understand some concepts related to predictive modeling. So let's say that I have the following data sample and am trying to regress sales on ...
1
vote
1answer
80 views

What is the optimal selling price of an item based on its historical price/volume data?

I'm trying to figure out how to price items on a market that appears to move randomly but within certain bounds. For example, here is a brief look at the time series data: ...
2
votes
0answers
41 views

Using sequential observations to perform online prediction

I'm trying to perform predictions from a sequence of events. My problem is this: Data collection: Suppose you can continuously observe a person sitting in a library. You take note of every time that ...
0
votes
0answers
47 views

Performing online prediction from sequential observations

I am trying to perform some predictions from a sequence of observable events. My problem can be abstracted like this: Data collection: Suppose you can continuously observe a person sitting in a ...
0
votes
0answers
50 views

Help with Algorithm Selection

I have asked this on the rapid-miner forum (http://forum.rapid-i.com/) but it can't hurt to get other opinions due to it not being a software-specific question. If this is the wrong section please let ...
2
votes
0answers
60 views

How to compare the accuracy of predictive algorithms when the predicted value contains measurement error

I am conducting (somewhat casual) research on the accuracy of several algorithms meant to compute a value when given a set of experimentally gathered variables, including time. The issue is, the true ...
3
votes
1answer
89 views

Clustering of count data

I am currently trying to find clusters in a data set that looks like this: ...
4
votes
1answer
389 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
116 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
32 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
63 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
125 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
93 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 ...