Forecasting involves estimating the value or distribution of a random variable which has not yet been observed.

learn more… | top users | synonyms (1)

0
votes
1answer
24 views

Predict time series data from another

Here is my problem: I have two times series which are highly correlated. One of my time series have one more data point. I would like to predict the other time series missing data. For example (in ...
0
votes
1answer
37 views

How is the error calculated in ETS using R?

I'm trying to replicate the ETS algorithms from R in Excel using the formulas present in the link below. https://www.otexts.org/fpp/7/7 According to my research the error is supposed to be ...
1
vote
0answers
17 views

Considerations for forecasting

I am trying to make a generic forecaster for many short (~14 points) to long term (~365 points) time series data assuming the seasonal period to be weekly. The predictions are going to be made for a ...
4
votes
2answers
31 views

Which forecast way is better

I want to predict daily headcount in a given area. The area can be divided into several blocks. The blocks share very little similarity. The question is, if I'm only interested in total daily ...
2
votes
0answers
31 views

Difference between different autoregressive models

I am trying to understand the difference between these three different specifications of an autoregressive model for variable "var" in STATA: ...
2
votes
2answers
52 views

Which econometric models can be used to forecast security returns + ARIMA/GARCH questions

I'm trying to write an undergraduate thesis wherein I test the predictive power of a given econometric model on a given financial time series. I need some advice on how I should go about doing this. ...
2
votes
1answer
62 views

Using the Weibull curve to model responses from a direct mail campaign. Model isn't fitting the data very well

I'm trying to build a model to forecast direct mail marketing campaign responses. In the "response" vector are the average number of responses from a marketing campaign from day 1 to day 63 (8 weeks). ...
4
votes
2answers
84 views

ETS() function, how to avoid forecast not in line with historical data?

I am working on an alogorithm in R to automatize a monthly forecast calculation. I am using, among others, the ets() function from the forecast package to calculate forecast. It is working very well. ...
0
votes
0answers
20 views

How to build separate time series forecasts model for each of 3k customers?

I have 3000 customers in my base and i want to forecast next 6 months revenue for each of these 3000 customers. Does that mean i have to build 3000 arima models 1 for each customer? I can build a ...
0
votes
0answers
13 views

Parsimonious Exponential Smoothing seasonality initialization

I have read the paper : http://users.ox.ac.uk/~mast0315/ParsimoniousSeasonalExpSm.pdf I am looking for a method that helps me forecast data at daily level and exhibiting double seasonality. First ...
5
votes
1answer
38 views

Minimizing symmetric mean absolute percentage error (SMAPE)

I am working on a forecasting application in which forecast errors are measured using the symmetric mean absolute percentage error: $$ SMAPE = \frac{1}{n} \sum\limits_{t=1}^n{\frac{|F_t - A_t|}{F_t + ...
1
vote
0answers
12 views

Product Mix vs. Sales

I work for a company that sells a small portfolio of products - we'll call them toasters. These toasters vary in quality and price, but all of them will toast your food. We have historic data on our ...
0
votes
0answers
27 views

Area under a curve- is there a way to find the % completion of a marketing campaign on a particular day?

I'm trying to build a model to forecast direct mail marketing campaign responses. In the code below I was able to use responses from a previous campaign to create a smooth curve (i.e. continuous ...
2
votes
2answers
29 views

Forecast encompassing test for cointegrated time series

I am forecasting an integrated time series variable $y_t$. I have two competing forecasts, $f^1_t:=f^1_{t|t-h}$ and $f^2_t:=f^2_{t|t-h}$. I would like to test whether $f^1_t$ forecast-encompasses ...
0
votes
0answers
33 views

I was able to use R to fit a curve to model direct mail marketing responses- just need the % of responses that are likely to occur each day

I'm trying to model the responses from a direct mail marketing campaign so that I can use it to forecast for future campaigns. In the code below, I started with the average number of responses by day ...
0
votes
0answers
20 views

pattern recognition or clustering for analyzing seasonal data

I have a set of historical data for an event which is highly seasonal. The event can be held in spring and summer but it is not planned for fall and winter. I wanted to forecast days to the next event ...
0
votes
0answers
28 views

How to decide about Regression Analysis or Time Series Analysis

How to decide about Regression Analysis or Time Series Analysis. ...
0
votes
0answers
17 views

non negative seasonal forecast using R

I am performing forecast of time series using the forecast package (ver. 5.9) of R. The characteristics of my time series are have hourly data (without holes) for about three months have daily, ...
1
vote
2answers
77 views

Forecast daily data with weekly and monthly seasonality using exponential smoothing

I have to forecast data that exhibits dual seasonality. For example, the first day of the week can show seasonality and also the first week of the month can show seasonality. I am planning to use ...
1
vote
1answer
53 views

How is $P[X_t\le x_t | X_1,\ldots, X_{t-1}]=P[X_t\le x_t]$ when $X_t\sim WN(0,\sigma^2)$?

In this slide , p.30 , p.31 , it is written that : White noise : $X_t\sim WN(0,\sigma^2)$ i.e., ${\{X_t}\}$ uncorrelated, $\mathbb E[X_t]=0, \mathbb V[X_t] =\sigma^2$ Example : i.i.d noise : ...
1
vote
0answers
8 views

Need some help on discrete valued time series forecasting?

I have data on reservation requests for hotels (your booking information:searching date, check-in, check-out, # of rooms and etc. on hotel booking websites) and am trying to do some analysis on one ...
0
votes
0answers
3 views

Gains Factors in Multinomial Regression Individual-level Forecast

I'm conducting a multinomial regression forecast of academic program enrollment based on individual-level data (i.e. data on students and those who are applying or otherwise indicating interest in ...
0
votes
0answers
10 views

How do you find out the number of intraday cycles for double seasonal exponential smoothing?

I have read about intracycle exponential smoothing in the paper Parsimonious Seasonal Exponential Smoothing. I am having trouble implementing the formula in Excel. It requires us to know the number of ...
4
votes
2answers
108 views
+50

On forecasting, the mean squared error and realized volatility

Say one has finished estimating a correctly specified GARCH(1,1) on a daily time series and now wants to evaluate the accuracy of the one step ahead forecasts what steps or tests could one do? I ...
2
votes
1answer
41 views

How to perform a simple smoothing forecast for next 12 months (using forecast package in R) [closed]

I currently have timeseries data (of gold prices) and I am trying to use a simple smoothing forecast to estimate gold prices for the next 12 months. I am not sure what function to use to accomplish ...
2
votes
1answer
54 views

Forecasting daily visits using ARIMA with external regressors

I have daily visitors data for the last 10 years. I want to do some basic tests like which is the busiest day, which is the busiest month, busiest week etc. I used ...
0
votes
0answers
5 views

trying to figure out how to make a suggestion given some input

I want to be able to express as a value (say 1-10 as an example), the strength of a suggestion that a person should do X tommorow. The rules are they should only do X in any 6 consecutive days out of ...
2
votes
1answer
122 views

Problems with time series prediction

I got a question about modeling time series in R. my data consist of the following matrix: ...
2
votes
1answer
187 views

R Time Series Forecasting: Questions regarding my output

I'm working on a forecast for the following data: ...
2
votes
2answers
51 views

Combination Forecast - Which models to pick?

Combination Forecasting can be produced by simply averaging different forecasts or employing more complex techniques (see Makridakis, 1989; De Gooijer and Hyndman, 2006; Goodwin, 2009; Pesaran and ...
0
votes
0answers
22 views

Getting Negative Forecasting Values [duplicate]

My data set in R contains the values like a b c 15 30 15 10 40 19 19 10 41 40 25 27 I have used the formula ...
2
votes
1answer
38 views

Providing 1 year monthly data (12 points), how to forecast next month

I got an interview question: Providing 1 year monthly data (12 points), can be traffic, product consumption, etc. How to forecast next month? I am confused. This question doesn't looks like a time ...
0
votes
0answers
28 views

Holt-Winters optimal parameters with gradient descent

Can we use gradient descent in order to find optimal alpha, beta and gamma for Holt-Winters model? And more generally, are there any academic works that suggest methods for finding optimal values for ...
0
votes
0answers
10 views

Conditional Expectation for Forecasting Intervention Model

William and Wei: Time Series Analysis Univariate and Multivariate Methods, Second Edition, page 90, gives the conditional expectation for $Z_{n+l}$ ($l$ step forecast of $Z_n$): $$ \hat{Z}_n(l) = ...
0
votes
0answers
39 views

root mean square error in forecasting

I have to use ARIMA model to forecast real prices of aluminium and copper in eviews. I have to do in sample and out of sample forecasting. my data set is annual from 1960 till 2014. I have selected a ...
0
votes
0answers
15 views

what is encompassing or nested models in forecasting?

I would like to ask what encompassing or nested models in forecasting means. I have a set of forecasts. A group of it is forecasted half hourly, so I have forecasts done a half an half an hour ago, ...
0
votes
1answer
30 views

How to align two seasonal time series

I am trying to decompose a time series using Holt Winters method and use it for forecast. I am trying to do this for weekly data of last 25-26 months. The challenge is that the dates of the seasonal ...
0
votes
1answer
42 views

Saving data into data frames in while loop for forecasting [closed]

I want to automate the forecasting procedure for a data set that I have. I have a three years of daily historic data and I want to use 2 years as test data and one year as train data. I want to have ...
4
votes
2answers
166 views

Reconstruction of Species Distribution based on poorly-sampled data

cross-posted to Signal Processing, World Building, and Biology Stack Exchange Problem: After reading a series of fantasy novels, I noticed that the biosphere in that world made no sense. To clarify, ...
0
votes
0answers
27 views

Interpreting tbats seasonal results for looking for the type of seasonality

Using tbatsfunction in R to look for seasonality. I test the seasonality for weekly and every 10 days and both have seasonality. ...
4
votes
1answer
138 views

Predicting the growth of traffic on a web site: regression or time series?

I've got a small website and I'm investing a lot of efforts on it. The traffic is growing but still very low. I've studied engineering but my knowledge of statistics is basic. I have put the last 70 ...
1
vote
0answers
27 views

Reorder point with stochastic lead time and demand

I'm trying to determine the optimal reorder point for some products. The reorder point must be greater than the demand during lead time a % of the times that I should determine, let's say 95%. ...
0
votes
2answers
38 views

arguments of length zero error with very similar code while forecasting

When I forecast from a linear Regression model in R using the following code, I get an arguments of length zero error , which I understand as a null pointer: ...
1
vote
0answers
23 views

Forecasting with use of PCA variables as independent and one ternary dependent variable in R

I'm having trouble in taking a direction of my research project. I have independent variables that are commonly used as economic indicators and I want to include variables/indicators that are not ...
0
votes
0answers
24 views

unable to perform holt winters forecasting on time series data

I am trying to perform a holt Winters forecasting for future dates in python. There is a working code but it only predicts one point ahead so at the end of the series, I only one more point for the ...
0
votes
1answer
77 views

ARIMA: How to interpret MAPE?

I am using the forecast package in R to generate an ARIMA model for my data. I started with the auto.arima function for a try and got a ARIMA(1,1,2) model. ...
5
votes
1answer
68 views

Can a forecast that reaches further into the future be less uncertain?

In Austrian television there is a weather show that gives temperature forecasts for the coming 15 days. They usually also provide uncertainty bands around that forecast which naturally makes the ...
1
vote
0answers
38 views

Which method to use for load forecasting

I have smart meter data set that has consumption readings collected over a year and a half for every 30 mins. What I am trying to do is short term load forecasting. The data set has just three columns ...
1
vote
1answer
44 views

What is the best lag length for auto correlation?

I am doing a monthly rainfall forecasting model. I have monthly data from 1998 to 2012. I found in previous research that they have used partial autocorrelations and stepwise regression as an input ...
0
votes
1answer
35 views

How to validate random walk model

I am studying ARIMA models and find it hard to validate the model in terms of "it's a good, useful model" and "I shouldn't use that model for prediction". So at first I started with the easiest ...