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

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3
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52 views

How are outliers dealt with in R after detected? [on hold]

Once outliers in time series are detected in R how exactly are they dealt with before forecasting? I dont want commands to use i would like the method. Please do not give any answers to do with ...
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0answers
21 views

ARIMA vs. Random Forest

We have some power load functions that of course are driven heavily by a workday rhythm that we need to forecast, and after some light research into the topic, I see that using ARIMA would seemingly ...
2
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1answer
108 views
+50

Putting less weight on certain data points in a series for forecasting

I have a data set that contains outliers (big orders) i need to forecast this series taking the outliers into consideration. I already know what the top 11 big orders are so i dont need to detect them ...
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3 views

Forecast joint distribution conditional on multiple external forecasts of marginal distributions?

I need to forecast the joint distribution of the vector $y_i(t+h)$, where $t$ is the time of forecast, and $h$ is a forecast horizon. For instance, $y_1(t+1),y_2(t+1)$ could be wind speed and the ...
2
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1answer
15 views

Exponential smoothing method that can be used in seasonal forecasting without trend

I'm working on the task of forecasting. The data I have is seasonal. I use exponential smoothing methods, but my references (e.g. for the Holt-Winters method) are for using such methods for seasonal ...
2
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1answer
27 views

Prediction intervals in ARIMAX accounting for forecast uncertainty in future $X$?

I have a problem with my SPSS software and ARIMAX forecasts. Consider a series $Y$ that depends on a different series $X$, which is not known in advance with certainty, but must be forecasted itself. ...
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1answer
22 views

Exponential smoothing state space model - stationary required?

I came across with the Exponential smoothing state space model for time series forecasting. My question is if it does require that the time series is stationary? Is there any paper that explicitly ...
0
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1answer
20 views

How to check if the data is intermittent or too many zeros are due to seasonality?

I have a dataset for weekly number of calls to a call center for three years.The data is seasonal (I know this from practitioners knowledge) which means that calls normally come on summer and winter. ...
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17 views

Forecasting With Random Forest in R [closed]

I have been Working with Forecasting the Daily Call Volumes in Call Center.Usually i use Seasonal ARIMA and TBATS(Exponential Smoothing State Space Models),but Sometimes it doesn't play Vital Role For ...
1
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1answer
132 views

R Time Series Analysis forecast result always remains same

I am trying to do time series analysis in R. I have data time series data set like this. ...
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0answers
43 views

Forecasting and decomposition of hourly time series with 2 seasonal periods

I have hourly temperature data over a 5 year period with a lot of missing values. They have 2 seasonal periods: daily (24) and annual (365*24). I am very interested in the diurnal cycles of the ...
0
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1answer
30 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
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1answer
46 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 ...
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0answers
18 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
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2answers
36 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 ...
3
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1answer
70 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
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2answers
63 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
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1answer
93 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). ...
6
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3answers
139 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
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0answers
22 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 ...
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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
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1answer
54 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 + ...
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0answers
13 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 ...
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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
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2answers
30 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 ...
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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 ...
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0answers
25 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 ...
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0answers
33 views

How to decide about Regression Analysis or Time Series Analysis

How to decide about Regression Analysis or Time Series Analysis. ...
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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, ...
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2answers
94 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
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1answer
55 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 : ...
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0answers
10 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 ...
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4 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 ...
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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
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2answers
140 views

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
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1answer
43 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
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1answer
58 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 ...
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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
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1answer
128 views

Problems with time series prediction

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

R Time Series Forecasting: Questions regarding my output

I'm working on a forecast for the following data: ...
2
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2answers
55 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 ...
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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
39 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
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0answers
35 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
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0answers
12 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
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0answers
41 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
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0answers
16 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
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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
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1answer
53 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
168 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, ...