0
votes
0answers
11 views

Stata: how do i set 2 time variables for 2 datas in 1 dataset? [closed]

I have quarterly data and yearly data in 1 dataset, how do I 'tsset' (time series) for both datas? (If it's even possible???) I do HAVE the quarterly data for the yearly data, would it be suggested ...
0
votes
0answers
43 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
64 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 ...
0
votes
0answers
15 views

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 ...
2
votes
2answers
107 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 ...
1
vote
3answers
157 views

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 ...
0
votes
1answer
28 views

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 ...
0
votes
0answers
27 views

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 ...
1
vote
1answer
48 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
24 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
36 views

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 ...
0
votes
0answers
12 views

How to get forecast using `stlf()` in R [migrated]

I am new to R. I am using the stlf() function in the forecast package to forecast trends in air passengers using the following code: ...
0
votes
0answers
15 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
88 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
112 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
0answers
24 views

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 ...
1
vote
1answer
177 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
65 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
19 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
62 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
0answers
32 views

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. ...
0
votes
1answer
42 views

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 ...
4
votes
1answer
93 views

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 ...
1
vote
1answer
68 views

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: ...
0
votes
0answers
31 views

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 ...
1
vote
0answers
34 views

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 ...
0
votes
2answers
99 views

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, ...
1
vote
0answers
72 views

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 ...
4
votes
3answers
252 views

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 ...
3
votes
2answers
94 views

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 ...
0
votes
0answers
29 views

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 ...
0
votes
1answer
89 views

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 ...
1
vote
2answers
97 views

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 ...
0
votes
0answers
62 views

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 ...
0
votes
0answers
18 views

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 ...
0
votes
1answer
46 views

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 $Y_t, t=1,...,T$. ...
3
votes
1answer
198 views

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 ...
1
vote
0answers
104 views

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 ...
0
votes
0answers
35 views

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 ...
1
vote
1answer
93 views

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 ...
6
votes
1answer
156 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 ...
0
votes
0answers
58 views

PACF and ACF for AR and MA

I once heard the following statement: ...
2
votes
1answer
62 views

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 ...
0
votes
0answers
56 views

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 ...
2
votes
3answers
196 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 ...
3
votes
1answer
50 views

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 ...
3
votes
2answers
207 views

ARIMA estimation by hand

I'm trying to understand how the parameters are estimated in ARIMA modeling/Box Jenkins (BJ). Unfortunately none of the books that I have encountered describes the estimation procedure such as ...
1
vote
0answers
51 views

are there any nonparametric forecasting methods?

Are there any good statistical non-parametric forecasting methods besides machine learing methods like neural netwworks/decision trees etc. for time series analysis ? If so, are there any R packages ...
0
votes
2answers
351 views

What are the assumptions of ARIMA modeling for forecasting time series?

What are the assumptions of ARIMA / Box-Jenkins modeling for forecasting time series?
0
votes
0answers
35 views

EMD-SVR method for time series

Has anyone attempted to use Empirical Mode Decomposition(EMD)-Support Vector Regression(SVR) in nonstationary time series forecasting? It seems quite interesting. As I observed it has high performance ...