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Questions tagged [forecasting]

Prediction of the future events. It is a special case of [prediction], in the context of [time-series].

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2answers
2k views

Two sample t-test vs regression

I would like to examine the difference in forecast error between year 1 and 2. The descriptive statistics show that the mean of forecast error is higher in Year 2 but the median is lower. Under what ...
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2answers
1k views

Flat ETS forecast of clearly increasing time series

I have a simple time series of one hour intervals: ...
8
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1answer
1k views

Jack-knife with time series models

Introduction I am aiming to forecast the annual growth rates for a number of macroeconomic indicators (denote one by $Y_t$). One of the tasks is to test the forecasting performance of rival time ...
5
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1answer
8k views

Regression with ARIMA(0,0,0) errors different from linear regression

A Regression with ARIMA errors is given by the following formula (saw on Hyndman et al, 1998): $Y_t = b_0 + b_1 X_{1,t} + \dots + b_k X_{k,t} + N_t$ where $N_t$ is modeled as an ARIMA process. If ...
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1answer
285 views

Discrete scenarios from an ARMA forecast

Given an ARMA model and a historical time series, I'm trying to create a set of $n$ forecast scenarios, where each scenario $s$ is a potential future hourly time series $x_s[t]$, with a given ...
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1answer
1k views

Linear regression forecast underestimation

I have the following multiple linear regression model: ...
7
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1answer
579 views

Disease forecasting - counts or rates?

I'm developing a forecasting model for an infectious disease for a hospital and wanting to understand if I should use disease counts or rates (based on population or total clinic visits). What are the ...
3
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1answer
558 views

Where did this risk exposure 'estimation-formula' come from?

I was reading a book and the authors metioned that risk exposure can be estimated scientifically using this forumula: $risk(\$) = \frac{(a + 4m + b)}{6}$ and standard deviation $\sigma = \frac{b-a}{...
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2answers
422 views

Estimate in presence of missing observations

I'm trying to estimate a parameter based on its past history. However, I do not have the observed data at every point of time. To illustrate the scenario, consider a group of N people where each ...
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1answer
1k views

Subset models in auto.arima function in forecast package

I wanted to ask whether it was possible to use the auto.arima function to identify subset ARIMA models rather than those of pure lags? I have identified a model in Stata in subset lags that performs ...
2
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0answers
101 views

Cyclostationary time series

http://en.wikipedia.org/wiki/Cyclostationary_process What are the methods in modelling and forecasting such time series? It is mentioned in the link above that there is a deterministic approach to ...
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3answers
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Combining two time-series by averaging the data points

I would like to combine the forecasted and backcasted (viz. the predicted past values) of a time-series data set into one time-series by minimizing the Mean Squared Prediction Error. Say I have time ...
3
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1answer
593 views

Forecasting a “chaotic” time series

Here are four graphs, 1, autocorrelation, autocovariance, partial-correlation and cross-correlation calculated from a time series are given. 2, The time series I need to do some predictions on ...
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2answers
437 views

Exploratory analysis of spatio-temporal forecast errors

The data: I have worked recently on analysing the stochastic properties of a spatio-temporal field of wind power production forecast errors. Formally, it can be said to be a process $$ \left (\epsilon^...
3
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1answer
318 views

Bracket Theory and Probability

So I apologize ahead of time if this isn't the correct venue for this question. I've been having a debate with a friend of mine for a few days now about what the best way to run a bracket is for a ...
3
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2answers
842 views

Understanding forecasting in R

I am presently trying to learn R. I would like to be able to apply it more in my work environment as I am an analyst in the Health Care industry. I am presently trying to use R to forecast. What is ...
3
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2answers
7k views

Problem in discrete valued time series forecasting

I have a temporally ordered discrete valued data. The only possible states for the data are: {1,2,3,4,5,6}. So the series is something like {1,2,3,5,6,4,3,5,2,......} I want to forecast the next value ...
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3answers
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How to forecast based on aggregated data over irregular intervals?

I am trying to forecast the sales of products in vending machine. The problem is that the machine is filled at irregular intervals and at every fill we only can record the aggregated sales since the ...
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1answer
4k views

Forecast with arima model [closed]

Starting with arima models in R, I cannot make a forecast with my favourite model. For example, the commands ...
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0answers
174 views

Calculation of seasonal (annual) component of time-series: use of cross-validation?

I've been working for almost a year on electricity load forecasting in collaboration with some climate scientists, using temperature data obtained from models. Instead of using directly temperature ...
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1answer
792 views

Example use of ARMA forecasting method

I have no experience in forecasting, so can anyone give me a step-by-step example or link to example-real values with ARMA forecasting method application?
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0answers
77 views

Calculate chance of big drop in a timeline

I am not much of a mathematics person, but I have been asked to create a program that will calculate a chance for a big drop on a timeline. I'm pretty sure even the way I try to explain it is not ...
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1answer
3k views

Random walk out of sample forecasting

Probably my question is a bit stupid, but I'm having some problems in writing down in R the out-of-sample forecasting with a Random Walk. I have a multivariate time series (y) and I want to estimate ...
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1answer
983 views

How can I perform weibull analysis on monthly recorded data of wind speeds?

I've read several articles about how to perform Weibull distribution but they all did it with wind speed data in a time series manner (example: recorded data every 10mins and then averaged to every ...
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1answer
164 views

ratio, MSE of basic demand to MSE of aggregated demand for MA(1) process

I have a basic demand series that follow MA(1) process,I've applied non-overlapping aggregation approach and then SES on both basic and aggregated series to obtain forecasts, and then I disaggregated ...
3
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1answer
442 views

Non-overlapping aggregation and autocorrelation

I have a time series that follow an MA(1) process , I do non-overlapping aggregation with aggregation level $m=2,3,\dots$, and then I calculate autocorrelation of basic and aggregated series, for ...
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1answer
1k views

h step ahead forecast

I have a problem consists of forecasting the next 16 values for 250 time series of daily demands, Can I forecast just for one period ahead and then multiple it by 16? is it correct? I was wondering ...
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0answers
187 views

Forecast and errors, dependent or independent

Assume the demand follows an MA(1): $$d_t=c+e_t-\theta e_{t-1},$$ Apply now, SES(single exponential smoothing)as a forecasting method. We know that the demand, $d_t$ is not independent. I was ...
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1answer
1k views

Dividing and forecasting a normal distribution

I have a collection of real-world samples that I am trying to model and then forecast. There are 10 datasets – each has an increasing number of data points (from 1 to 10). The points are equi-...
2
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2answers
961 views

Time Series representation and forecasting in R

I have to forecast a time series in R of a Internet network traffic bitrate. The data are in file http://www.forumaltavilla.it/joomla/datitesi/dati.dat and the sampling time is every 0.05 seconds. Now,...
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1answer
3k views

Estimating out-of sample forecast for an ARIMA model

I’m trying to estimate the out-of sample forecast of an ARIMA model, I tried the code below, but it totally doesn’t work! ...
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2answers
204 views

How to model the relationship between geocoded and ungeocoded sales data?

I am trying to model sales data for stores at the Census block group level in order to predict sales at potential new restaurants. For example, I know that store 2, which has a giant flashing neon ...
1
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1answer
185 views

Lemonade consumption forecast

Some guys, decided to make some money, by selling lemonade in different public places. Each guy has a fix spot on which she sell the lemonade. In every morning, they go to a lemonade maker warehouse ...
13
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1answer
4k views

Calculating forecast error with time series cross-validation

I have a forecasting model for a time series and I want to calculate its out-of-sample prediction error. At the moment the strategy I'm following is the one suggested on Rob Hyndman's blog (near the ...
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1answer
172 views

Computational intelligence-based methods for time series forecasting?

I know that ARIMA is one approach widely used in forecasting of univariate time series. What are some computational intelligence based methods that are reported to be successfully used in the same ...
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2answers
2k views

Time series data distribution forecast?

While having chronically data of population growth (registered users of a site), I want to compute a function that approximates future growth, based on past data. Also, what we ll be the distribution ...
0
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1answer
540 views

How to set the seasonality length to 7 using the ets function in R?

I am new to R and am hoping to use ets from the forecast package to forecast daily data which has a weekly pattern. Is there ...
4
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2answers
527 views

Is the Kalman filter actually forecasting?

The state space equation is: $$Y_t = F_tθ_t + v_t\hspace{4em} \textrm{eq. 1}$$ $$θ_t = G_tθ_{t-1} + w_t\hspace{2.8em} \textrm{eq. 2}$$ $F_t$ in eq.1 are the independent variables and we can predict ...
3
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2answers
349 views

How to accurately quantify forecast uncertainty in a special case of robust linear regression?

If I'm using OLS linear regression, and I want to know the uncertainty of my forecasts I can quantify it using residuals (MSE, median absolute deviation, etc). But if I'm using robust linear ...
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2answers
1k views

Constructing a naive recession forecast

I am testing a variety of models to produce 1-month ahead predictions of US Recessions. To benchmark these models, I want to build a naive recession model. My first thought was to use the current ...
7
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1answer
896 views

How to predict future reservations when data for the current day is incomplete?

I'm trying to build a model to predict reservations up to 15 days in advance. So, if I want to predict how many reservations there will be tomorrow, I use historical data of how many total ...
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1answer
420 views

The most suitable ARMA software [closed]

what is the most appropriate software for building an ARMA forecasting model? EViews, Minitab,...? Best, Milos
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2answers
3k views

Prediction with GLS

Let's say I build a Generalized Least Squares model. I follow the standard procedure and first estimate a LM model. Then I create an error-response covariance matrix based on the residuals of this ...
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5answers
2k views

Can data cleaning worsen the results of statistical analysis?

An increase in the number of cases and deaths occurs during epidemics (sudden increase in numbers) due to a virus circulation (like West Nile Virus in USA in 2002) or decreasing resistance of people ...
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1answer
142 views

Proving significantly better performance in binary forecasting

I have two different algorithms that make forecasts for binary events. The observed result can either be 1 or 0 (like "rain" or "no rain"). The algorithms usually give a forecast in the 0.4-0.6 range. ...
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2answers
3k views

Forecasting stock prices time series based on independent factors using ARIMA model

I am trying to forecast time series of stock for a particular case in which closing value of the stock depends on independent factors which is in which infact another time series. Situation is like I ...
4
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2answers
206 views

What can you do with 'crazy' data?

This question is more about an approach to a complicated data situation rather than particular statistical methods. I'm modeling our organization's electricity bills, and I have monthly billing data ...
6
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1answer
252 views

Coefficient / model averaging to control for exogenous circumstances in prediction

I'm interested in exploring statistical models (or modifications thereof) designed to handle a specific type of problem. Due to my ignorance of statistical terminology, I can only describe this type ...
6
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2answers
5k views

What methods to use for statistical prediction/forecast of trading data?

I’m working on a trading system and need to apply some statistics on the results. Unfortunately I forgot all about statistics after I left university over a decade ago and now I really have no clue ...
2
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1answer
230 views

Deriving risk estimates using forecasting confidence limits and out of sample hold-out cases

I was hoping for some advice. I use SAS for automatic forecasting (I have a large number of forecasts to complete in a limited timeframe). As part of the forecast output from SAS, I get a mid-point (...