0
votes
0answers
28 views

What types of statistical analysis technique available to compare two different time series [on hold]

I am currently looking for suggestion to compare or study the two different period time series like sales in 2000 and 2001. As it is sales of the same product and i would like to compare those two ...
0
votes
0answers
9 views

package in R for BMA of a logistic model?

I am trying to perform analysis similar to Gerlach et al. (2002). it involves predicting the posterior probability of a particular binary outcome using the previous 5 observations. I was just ...
2
votes
1answer
48 views

R: forecast function accuracy for ARIMA models

I have a problem with the forecast function for ARIMA models in R. It calls predict that calls ...
0
votes
0answers
13 views

Can I include future index into current forecasting in R models

I am new to R. Now my team is building forecasting models for monthly sales. Our sales correlates quite well with a industry index. As a forward index, we can get both past 5 years' index and next 3 ...
0
votes
1answer
29 views

Alternative to forecast() and ets() in Python?

I'm looking for a Python alternative to R's ETS() from forecast(). It's my understanding that ETS() is one of the best performing forecasting program and I would like to use it. However I am ...
0
votes
0answers
19 views

Obtaining the Psi Weights of a seasonal ARIMA in R

I am trying to quantify the effect of a future random shocks on my seasonal ARIMA model. If I have understood the theory correctly, the easiest way is to express my seasonal ARIMA model in its "random ...
0
votes
0answers
44 views

Arima model - multi step forecast

The following code shows a forecast of the next 24 hours of my electricity prices with two exogenous variables. My problem is, that I don't know how to build a forecast for the next 3 days or more ...
0
votes
1answer
33 views

MAPE is high for daily sale prediction

I have daily sales data from 2011 to 2013. I have to do prediction for 2014.I have used arima and exponential method to predict the daily sale, but it is not giving the better result. MAPE is around ...
0
votes
0answers
38 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
26 views

Kalman Filter Correction efficiency

I was wondering if Kalman Filter used in a way to correct and reduce forecast errors is useful in real life forecast.Since we are using output forecast data and measurement data from t-1 to correct ...
0
votes
1answer
56 views

How to forecast time-series bounded by [0,1], i.e., forecast relative frequencies?

I am working with time series values which are all in the closed interval [0, 1]; these values represent relative frequencies, i.e., empirical probabilities. I would like to create a model such that ...
1
vote
1answer
37 views

Combinef in R HTS package- constrain to keep forecasts positive?

When using the combinef function from Rob Hyndman's very useful hts package for forecasting hierarchical and grouped time series, there does not seem to be a way to constrain the optimally combined ...
1
vote
1answer
52 views

Forecasting a time series with weights

I'd like to forecast (or predict) a time series with weights. The following works using the regular linear modelling techniques ...
1
vote
0answers
87 views

Forecasting using auto.arima

I have the weekly revenue data for an electronics company the decomposed plot of which is as follows: I have decided to keep the seasonality and apply a suitable forecasting technique. I tried ...
0
votes
0answers
57 views

Removing seasonality from data

I have a dataset depicting weekly revenue over time for a computer company. The plot for the data looks like this: I decomposed the data into its additive components using the ...
0
votes
0answers
64 views

Forecasting in R using forecast package

I'm trying to forecast hourly data for 30 days for a process. I have used the following code: ...
0
votes
1answer
90 views

Machine-Learning algorithms for Forecasting

For work, I'm working on an app where you essentially forecast the failure rate of the overall machine through different factors such as the historical failure rates for the components used to build ...
0
votes
1answer
59 views

Implement different variation of Holt Winter technique using R for 52 weeks of data

As per my job requirement I have to do forecasting using only Holt Winter technique in R.I have weekly data for 2 and half years & I have to predict weekly.I'm planning to build time series with ...
1
vote
0answers
28 views

What method(s) should I use to achive statistical ranking?

I'm attempting a project where I need to statistically rank available cars based on several variables such as cost, mpg, seating, milage, etc.. I wish to rank these cars in order decide which car ...
0
votes
0answers
40 views

Plotting a Probit Time Series in R

I've searched around a bit, but am having trouble finding an answer to my specific question that isn't too technical. I want to predict the probability that we are at a turning point – arbitrarily ...
1
vote
0answers
53 views
0
votes
1answer
33 views

How can I use the results of GARCH in order to improve a forecast?

I am kind of confused with what I should actually do with predicted volatility values that I obtained via a ARCH/GARCH model other than feeling happy that I know when volatility rises/falls. Is there ...
0
votes
1answer
54 views

dlmForecast function in dlm R package forecasting constant values for seasonal series

I have a question regarding the use of the dlm CRAN package for forecasting values of a seasonal time series. I've built a dlm model combining a stochastic local level model with a stochastic ...
0
votes
0answers
36 views

Interpretation of TBATS Components

I've searched everywhere for this answer, and come up empty handed. I'm building a forecasts model for interface traffic reported in 5 minute intervals over a 1 year period. To account for ...
0
votes
1answer
117 views

How to forecast multivariate time-series 'accurately' with a large number of unknown factors using R?

I am relatively new to statistics and not formally trained but have been given a complex problem to solve and need some guidance. I realise that I am out of my depth a bit here but would appreciate ...
1
vote
0answers
69 views

What are the latest methods to generate ensembles?

I am working with ensembles, and I'm willing to go deep inside the work. I have historical records of: Observations of one variable Historical forecasts for the same variable For future ...
3
votes
2answers
49 views

Forecasting irregular pattern and volume

I have tried a number of different models to forecast the time series shown below, but so far I haven't found any models that satisfy me. I am looking for ideas for a suitable model. The objective ...
0
votes
0answers
18 views

Forecasting daily online visits in r [duplicate]

We have three years of data for online visits at a daily level. We want to forecast the daily visits for the next 90 days. What would be the best method to capture weekday seasonality , holiday ...
0
votes
3answers
123 views

Daily forecasting

We have three years of data for online visits at a daily level. We want to forecast the daily visits for the next 90 days. What would be the best method to capture weekday seasonality , holiday ...
1
vote
1answer
62 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 ...
0
votes
0answers
22 views

Suggestions - forecasting models

I have been assigned a task where I need to solve a business case. Let me explain what information I am looking for: I have historical data of several products and I need to forecast the time ...
1
vote
1answer
145 views

Missing Values NAs in the Test Data When using predict.lm in R

I have two data sets Train data Test data (with no dependent variable values but I have data on independent variable or you can say I need to forecast). Using the training data (which has some ...
2
votes
0answers
73 views

Forecasting call volumes over short intervals using R

I am trying to do a basic forecast of call volumes using the forecast library for R. I am not having too much trouble forecasting on a daily or monthly interval, however when I try to forecast on an ...
6
votes
0answers
193 views

Multivariant time series in R. How to find lagged correlation and build model for forecasting

I'm new in the page and pretty new in statistics and R. I'm working on a project for college with the objective of finding the correlation between rain and water flow level in rivers. Once the ...
1
vote
2answers
101 views

How to produce the minimum forecast error using R?

Considering that we want to use optimize() on the interval [0,1] how can I write an R code for finding the value of β that produces the minimum forecast error without using external packages like ...
0
votes
0answers
34 views

How to compare forecasting methods: based on ARIMA and curve fitting?

I'm making a project connected with identifying the dynamics of sales. My database concerns 26 weeks (so equally in 26 time-series observations) after launching the product. I want to make forecast ...
1
vote
1answer
47 views

Strange results in Holt forecast

I am trying to understand what could be causing these strange values to appear on applying a Holt model to a vector. The data represents actual sales of an item. ...
0
votes
0answers
85 views

What is the difference between forecasting based on ARIMA and logistic curve? R

I'm making a project connected with identifying the dynamics of sales. My database concerns 26 weeks (so equally in 26 time-series observations) after launching the product. This is what my database ...
1
vote
1answer
140 views

Forecasting with holiday dummy variables

I have an example of call center data for 2013. There are 261 days of data (excluding weekends). For 2013, I have included a holiday dummy variable (holiday) for ...
2
votes
2answers
169 views

Special method for forecasting on time-series clusters in R?

I'm doing a project related to identifying sales dynamics. My database contains 26 weeks after launching the product (so 26 time-series observations equally spaced in time). I used two methods ...
0
votes
1answer
110 views

Want to make a function which allows for recursive window forecasting

I have been looking for a function that can make recursive window out-of-sample forecasts, but seems there is none. So I'm thinking about about making a function that can be used for recursive window ...
0
votes
0answers
32 views

Forecast mean and variance for group data

Apologies if this is a bit of a simple question, but I haven't been able to find any answer to this over the past week and it's driving me crazy. Background Info: I have a dataset that tracks the ...
0
votes
0answers
22 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 ...
0
votes
1answer
331 views

R time-series forecasting with neural network, auto.arima and ets

I've heard a bit about using neural networks to forecast time series. How can I compare, which method for forecasting my time-series (daily retail data) is better: auto.arima(x), ets(x) or ...
1
vote
0answers
323 views

Forecasting daily data with trend, yearly, day of the week, and moving holiday effects

I'm expanding a question I posed earlier because I think it was lacking detail. I'm attempting to forecast daily demand for a restaurant that sells take away food, primarily to office workers on ...
1
vote
1answer
296 views

Time series forecasting using R

I have many time series(retail data). Some with trends, some seasonal, and some with neither. With period day, week or month. I need to make forecast, for each time serie. I'm looking for the most ...
2
votes
1answer
133 views

Forecasting irregular time series (with R)

There are several methods to make forecasts of equidistant time series (e.g. Holt-Winters, ARIMA, ...). However I am currently working on the following irregular spaced data set, which has a varying ...
0
votes
0answers
28 views

R: One period our cross validation with time series

I have quarterly data with one causal variable (X) and one dependent variable (Y). 30 such observations. I have the X variable for a quarter, and I'm seeking to predict that quarter's Y. The ...
1
vote
0answers
286 views

Time series modeling with R on weekly data

I am trying to do time series modeling and forecasting using R based on weekly data like below - ...
0
votes
1answer
67 views

Why are fitted values different from one-step ahead forecasts?

Let's say I fit an ARIMA model on a time series up to date t. I want to forecast the 10 next values without refitting the model but also using the latest data available for each date. So forecast ...