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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1answer
2k views

Estimation of white noise parameters in Gaussian random walk model

I want to estimate the parameters (mean , variance ) $e(t)$ for the random walk model $X (t) = X (t-1) + e(t)$. (where $e(t)$ is the white noise with a Normal distribution). By using the fact that ...
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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 ...
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0answers
1k views

Relationship between $R^2$ and MAE in forecasting

I have the following linear model based on multivariate timeseries: ...
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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 ...
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413 views

Help choosing the optimal time series analysis package

I am developing an app for time series analysis that should support the following: Exponential Smoothing (Holt-Winters) Box-Jenkins curve fitting (straight line, quadratic, exponential, growth) ...
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1answer
18k views

How to decompose a time series with multiple seasonal components?

I have a time series that contains double seasonal components and I would like to decompose the series into the following time series components (trend, seasonal component 1, seasonal component 2 and ...
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2answers
682 views

Forecasting the target variable vs building a causal model and forecasting causal variables

I want to know the approaches people use to forecast lets say unemployment rate .... By itself it might not fit a time series model (ARMA) very well as the trend is dependent on many external factors. ...
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4answers
873 views

What method is suitable for short-term forecast for a trendless, oscillatory, bounded time series?

I am new to time series analysis and I would appreciate if anyone could provide me some insight on it. I am trying to analyse a past series of numbers that fluctuates between 107 & 210 with a ...
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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
970 views

Least stupid way to forecast a short multivariate time series

I need to forecast the following 4 variables for the 29th unit of time. I have roughly 2 years worth of historical data, where 1 and 14 and 27 are all the same period (or time of year). In the end, I ...
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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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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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3answers
7k views

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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2answers
1k views

Residual analysis of cross-sectional time-series forecasts

I have forecasts and actuals for panel data (i.e. time-series cross-sectional data). The forecasts are already generated and provided by some source outside of R. I'd like to evaluate the quality of ...
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1answer
1k views

Seasonally adjusted month-to-month growth with underlying weekly seasonality

As a side hobby, I have been exploring forecasting time series (in particular, using R). For my data, I have the number of visits per day, for every day going back almost 4 years. In this data there ...
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4answers
4k views

Assessing forecastability of time series

Suppose i have a little over 20.000 monthly time series spanning from Jan'05 to Dec'11. Each of these representing global sales data for a different product. What if, instead of computing forecasts ...
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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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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
1k views

Using rolling windows to compute out of sample accuracy

I’ve already written this question, but probably I didn’t specified it well, for this reason I write it again. I need to use a random walk model (no-change) yt = yt(1+t) to compute the ratio of RMSFE. ...
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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
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 ...
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1answer
982 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
440 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
2k views

Using a time series model to forecast future values in R

I would like to use a set of weather-related historical data to fit a time series (let's say 1970-2000, Fourier terms plus ARIMA terms), but then use the fit on recent data (i.e., the last week/month ...
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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-...
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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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1answer
4k views

Automated parameter selection for a GARCH model, in a similar manner to the forecast package

I was wondering: is there are a package in R for automated GARCH model selection? I'm thinking of something like what the forecast package does for ARIMA models. If I implement this myself, would it ...
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3answers
2k views

Time Series detrending with multiple polynomials

I'm currently working on energy demand forecasting using daily load data. I'm using data since 1990 and, in order to use ARIMAX models, I detrended the data (using a first-order polynomial) and then I ...
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1answer
1k views

Characteristics of gold prices in an ARIMA model analysis

I'm forecasting gold prices using an ARIMA model. An ARIMA model requires a stationary, non-seasonal, linear series. However, after reading a few books, it seems that gold price data is nonstationary,...
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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 ...
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1answer
256 views

How to combine the forecasts when the response variable in forecasting models was different?

Introduction In forecasts combination one of the popular solutions is based on the application of some information criterion. Taking for example Akaike criterion $AIC_j$ estimated for the model $j$, ...
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3answers
212 views

Combining expert estimates

I am trying to work on a process to improve how how well my team estimates. I want to look at using some statistics to help out and embrace the uncertainty in how we estimate tasks. If I have a group ...
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3answers
7k views

Recurrent neural networks in R

I've heard a bit about using neural networks to forecast time series, specifically recurrent neural networks. I was wondering, is there a recurrent neural network package for R? I can't seem to find ...
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3answers
2k views

Univariate time series forecasting based on auto.arima

I have univariate time series data (windspeed at a particular place) measured at 1 hour interval for 5 years. I used auto.arima() to get the following parameters: ...
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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 ...
3
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1answer
591 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
2k views

Transformation for stabilizing variance in time series

In most forecasting packages there are two transformations easily available for stabilizing variance: the square root and the logarithnic. Is there any procedure (e.g. test) that can tell the user ...
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3answers
10k views

How do I calculate projected figures for the next year based on past performance?

I'm a SQL/C++ developer who recently has been asked to generate a report from our database to predict some future performance based on historical data; the problem is that I don't have much experience ...
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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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8answers
11k views

What algorithm could be used to predict consumables usage given data from past purchases?

Thinking about a supposedly simple but interesting problem, I'd like to write some code to forecast consumable I'll need in the near future given the full history of my previous purchases. I'm sure ...
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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
845 views

Compare modeled (fitted) paired data to actual data in forecasting problem (Excel sheet included)

In my endeavor to learn forecasting and improve my statistical knowledge, I've decided to forecast the population of a certain area. I've attached the excel file that I used. I know I'm using excel ...
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1answer
2k views

Good practices when doing time series forecasting

I've been working for months on short-term load forecasting and the use of climate/weather data to improve the accuracy. I have a computer science background and for this reason I'm trying to not make ...
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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 ...
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2answers
2k views

Proper ways to perform time series and ARIMA

Note that I do most of my analysis using R and Excel. Let's take this data set for example. I modified it as the data itself is proprietary: the years are also different: ...
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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 ...
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6answers
16k views

What is the best software for time series analysis and forecasting?

Is MATLAB better than R for time series analysis and forecasting or vice versa? What other software is considered best for time series analysis?