0
votes
0answers
14 views

Stock Closing price forecasting using ARIMA Model in R ( Entry level R programmer and Statistics learner)

I am an entry level R programmer and trying to learn statistics. i have downloaded the daily stock Adjusted Close price of one stock from sep 2011 to till date. As per my study plan, i have plotted ...
0
votes
0answers
11 views

TBATS missing value error

I used tbats to find the best fit model to a 3 years of daily data. It couldnt find a model and showed the following error: " Missing values encountered. Using longest contiguous portion of time ...
1
vote
1answer
23 views

How to compute RMSE for TBATS

Some forecasting models in R give error terms as their output. But for TBATS, I couldnt find out that how I can see what the RMSE for my data set is. Is there any specific command that I have to use ...
0
votes
0answers
17 views

Testing the accuracy of transformed data

I have run my data through a model in r, i ran ARIMA to forecast. The model forces a log transformation to be applied to the data. To test the accuracy of the fitted model formed by ARIMA would i need ...
3
votes
1answer
41 views

Difference between the forecast and simulate functions in the {forecast} package in R

I have been using the forecast package in R to make forecasts based on an ARIMA model and have noticed a difference in the output of the forecast and simulate functions when calculating confidence ...
1
vote
1answer
35 views

No fitted ARIMA model

I wanted to fit an ARIMA model to a daily database for three years but auto.arima couldn't find a model and showed the following error: ...
2
votes
1answer
62 views

Forecasting a seasonal time series in R

Forecasting airline passengers seasonal time series using auto arima Hi, I am trying to model some airline data in an attempt to provide an accurate monthly forecast for June-December this year using ...
1
vote
1answer
36 views

Transforming a time series with a negative number

I have been given data to forecast however it has a negative figure within the data which then, when doing a log transformation to make the series stationary, the ARIMA script i have written won't ...
0
votes
0answers
18 views

Panel data forecasting from Arellano-Bond GMM estimation

I want to come up with predictions of final energy demand per capita (fe) for a panel of countries. Explanatory variables are GDP per capita (gdp) and population density (pop) -- all variables are ...
2
votes
1answer
27 views

standard errors of the fitted values of a time series regression

I really want to understand how the math is working here. I am trying to get the standard error of the fitted values for a time series regression model.In the non-time series regression,I know I can ...
1
vote
1answer
55 views

Forecasting at individual versus grouped level

I have monthly usage data (spanning 3 years) for a customer base of around 200K, and I need to generate 1-month ahead forecasts for each of them. There are a couple of exogenous variables that would ...
3
votes
3answers
55 views

Transforming time series to compensate for change in variance

I have a time series (shown below) that comes from a sensor whose calibration was changed in the middle of last year. As part of this change, the sensor's reading of the variance (or volatility) of ...
0
votes
0answers
28 views

Reproducing ARIMA error terms

When forecasting a moving average (MA) model using R's forecast, why does using residuals(fit) produce different results than ...
0
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0answers
21 views

Time series Data Analysis and Forecasting by country and time factor

cty year qtr tl Argentina 2009 Q4 3 Argentina 2010 Q1 2 Argentina 2010 Q2 7 Argentina 2010 Q3 7 Argentina 2010 Q4 10 Argentina 2011 Q1 7 Argentina 2011 Q2 7 Argentina 2011 Q3 1 Argentina 2011 ...
0
votes
0answers
13 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
72 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
38 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
22 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
52 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
34 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
44 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
30 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
69 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
39 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
70 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
101 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
65 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
75 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
100 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
72 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
41 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
67 views
0
votes
1answer
37 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
67 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
49 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
137 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
70 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
52 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
136 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
68 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
24 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
177 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
76 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
216 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
108 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
36 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
50 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. ...