# Tagged Questions

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### 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 ...
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### 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 ...
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### Is there any tool that can do Vector ARIMA modeling in time series

Vector ARIMA model is used in multiple time series analysis. I am just wondering if there is any software or tool can be used to build the model. Some tools,like R, can only be used to predict the ...
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### Using results of regression on raw observation values to approximate results of regression on relative change between observations (Simple, Linear)

this is my first time on Stack Exchange so if I did something wrong please tell me. I have a time series dataset. There is an observation $(y,x)$ for each continuous time $t$. Let’s say for each day ...
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### 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 ...
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### 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 ...
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### Wavelets with forecast model

I am new to wavelets decomposition technique and am trying to use it with time series model. What I use now is that use discrete wavelet transform. I use Daubechies with 4 as mother wavelet with ...
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### 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 ...
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### Developing an appropriate time series model to predict sales based on past month record

I have been operating an online business for two years in a row now, so I have my monthly sales data for about two years. My business for every month is certainly affected by seasonal swing ( performs ...
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### Constant forecasts in SPSS

I have weekly data for the last four years. I am using SPSS to do forecasting. I am getting a constant value in the forecast period. What could be the reason behind it? Is it due to defining weekly ...
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### Time series forecasting using genetic algorithms

I am a beginner in the field of forecasting. I wish to know which are the best tools that can be used for forecasting future values in a time series using genetic algorithms. Are there any tools in ...
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### 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 ...
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### 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 ...
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### Forecasting daily electricity price

I'm trying to make a model to forecast the electricity price, a time series model with R and i have some questions Our data are daily price of the past 3 years from north pool countries, and we are ...
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### 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 ...
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### 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 ...
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### 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 ...
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### Daily Sales Data - Week Days Only, No Holidays

I'm trying to predict the daily sales for a take out restaurant. They are located in the downtown core of a large city. Their primary customers are office workers on their lunch breaks, and as such ...
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### 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 ...
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### 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 ...
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### 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 ...
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### 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 - ...
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### fpp forecasting using AWS ubuntu

Is the package fpp (or any of its previous incarnations like forecast) supported in Ubuntu 12.04 using AWS? It is the only package that R downloads but when you load the library it throws an error. ...
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### NIST exponential smoothing formula

I am trying to relate data and results in NIST website with the formula defined in previous page from the same website. But I am missing something here: Does initial trend & season indices ...
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### Holt-Winters exponential smoothing formula

I am trying to implement Holt-Winters exponential smoothing in Java program (I understand that R and Python have implementations of these algorithms, but I can't use those due to other reasons, so ...
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### How to get the true mean forecast using the Arima package with a Box-Cox transformation

In the Arima package, using a Box-Cox transformation give wrong results when later applied to the forecast method. For example, consider this data: ...
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### Using Real-Time Forecast Errors to Improve Forecast

I'm trying to forecast customer orders, and want to incorporate real-time forecast errors into my forecast. Say it's Monday, and I forecast that the customer will order 100 units on Wednesday. To ...
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### On the Fly Time Series modeling

I'm dealing with a system which monitors and records a time series (half hourly) which I plan to use to build a double seasonal time model (if possible using something that already exists, such as ...
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### step by step tutorial for newbie

I'm looking to join the field of statistics and more exactly to forecasting. I'm a software developer and I just started playing with R. Can you recommend me some tutorials related to forecasting, ...
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### What is the frequency of a time series for hourly data?

I am using R for time-series analysis and predictions, the package 'forecast' to be more precise. I am in a dilemma. I have hourly data that needs a prediction and needs to be analysed. I am using the ...
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### Performing a time series ARIMA model on natural gas power demand using the forecast package from R

I've been attempting to forecast natural gas power demand and how it is affected by temperature and price. I'm not sure if I have done everything correctly (relatively new to R), but I do seem to get ...
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### Is this a valid application for a Kalman filter?

I have 2 time series; Both the series are tracking inflation.(they have different sampling frequencies) Blue is the official CPI released by the US government. Red is an independent group's measure ...
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### A question on transfer modeling for the intervention analysis of time series data

When reading the section of intervention analysis of time series, I have one question regarding the following descriptions. The following graph defines several response patterns for step function ...
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### Using Moving-average smoothing in forecast package [closed]

I tried to use the non-centred moving average, that means just using past values by setting the option centre = FALSE, but unfortunately you get the centred results. Can anyone detect the failure ...
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### Which forecasting method should be selected in case of contradictory results from different accuracy measures?

I'm comparing some forecasting methods using four accuracy measures: Mean Absolute Error (MAE), Mean Squared Error (MSE), Mean Absolute Percentage Error (MAPE), Mean Absolute Scaled Error (MASE). The ...
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### Forecasting time series with trend and seasonality

I have a univariate time series, which has a trend and month seasonality. Traditionally I have been using auto.arima() method in R to model such series. So when I ...
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### Estimating effect of binary event on multiple time series

I have multiple time series where at any point in the time series, an event can occur that I believe has an effect on the time series. This event can happen at different times for each of the ...
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### Forecast model developed now, but only used later, is it still valid?

I am not sure what the appropriate title for my question is, so I am open to suggestion/correction. Now, the question: I observed a daily series $X_t, t=1,...,T$ also series $Y_t, t=1,...,T$. ...
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### time series dimensionality reduction

I have a call center data (such as one below) that has call data collected every 15 minutes. For a day the periodicity is 96 and for a week the periodicity is (7 x 96 = 672). If I would like to ...
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### R - ARIMA model with long seasonal periods - Error: “length of x and xreg does not match”

i want to use an ARIMA model in R for predicting an electrical load on a minutely basis. By examining the ACF I figured out which model could suit. The ACF has shown that the value one day ahead has a ...
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### Is there a formula to find the MAPE for $Y_t$ if we know the MAPE for $\Delta$log($Y_t)$?

Is there a simple formula to find the MAPE for $Y_t$ if we know the MAPE for $\Delta$log($Y_t)$ ~ iid N($\mu$,$\sigma^2$)? Is there an algebraic relation between the two? What if I use RMSFE ...
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### Given this time series, what statistical methods would be used for description and forecasting?

These static cumulative default rate tables and charts come from this public report published by a credit rating agency. Basically, you take all the loans originated in a period of time (a ...
158 views

### How to achieve strictly positive forecasts?

I am working on a time series whose values are strictly positive. Working with various models including AR, MA, ARMA, etc, I couldn't find an easy way to achieve strictly positive forecasts. I'm ...
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### PACF and ACF for AR and MA

I once heard the following statement: ...
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### Why is the expection of $E(Y_{T+1}|\Omega_T)$ greater than or equal to its previous value?

Consider the following model for $Y_t$: $\Delta$log($Y_{T+1})$ = $u_T$ where $u_T$ ~ IID Normal(0,$\sigma^2$). I want to forecast $Y_{T+1}$. Taking exponentials and then expectations, we see that ...
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### Is my understanding of estimation correct?

I have two time series, $y$ and $x$, where $y$ is sampled monthly and $x$ is sampled daily. I plan to use a mixed frequency regression(MIDAS) where I assign custom weights to the daily data points in ...
203 views

### Does ARIMA require normally distributed errors or normally distributed input data?

I have two questions related to time series forecasting with ARIMA: Does ARIMA require normally distributed errors or normally distributed input data ? Are there any assumptions on input time series ...
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### Time series forecasts of appointments with pre-registration

Looking for some tips and ideas. I get a list every day of the number of appointments for each day for the next two weeks for a clinic. I have quite good history of these list, and the actual number ...