Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Approaches for multi-step density forecasts with application to
  aggregated wind power   The generation of multi-step density forecasts for non-Gaussian data mostly
relies on Monte Carlo simulations which are computationally intensive. Using
aggregated wind power in Ireland, we study two approaches of multi-step density
forecasts which can be obtained from simple iterations so that intensive
computations are avoided. In the first approach, we apply a logistic
transformation to normalize the data approximately and describe the transformed
data using ARIMA--GARCH models so that multi-step forecasts can be iterated
easily. In the second approach, we describe the forecast densities by truncated
normal distributions which are governed by two parameters, namely, the
conditional mean and conditional variance. We apply exponential smoothing
methods to forecast the two parameters simultaneously. Since the underlying
model of exponential smoothing is Gaussian, we are able to obtain multi-step
forecasts of the parameters by simple iterations and thus generate forecast
densities as truncated normal distributions. We generate forecasts for wind
power from 15 minutes to 24 hours ahead. Results show that the first approach
generates superior forecasts and slightly outperforms the second approach under
various proper scores. Nevertheless, the second approach is computationally
more efficient and gives more robust results under different lengths of
training data. It also provides an attractive alternative approach since one is
allowed to choose a particular parametric density for the forecasts, and is
valuable when there are no obvious transformations to normalize the data.

10
The categories of this paper are: q-bio
37
The categories of this paper are: supr-con
26
The categories of this paper are: bayes-an
24
The categories of this paper are: dg-ga
4
The categories of this paper are: cond-mat
18
The categories of this paper are: econ
28
The categories of this paper are: alg-geom
2
The categories of this paper are: math
14
The categories of this paper are: math-ph
12
The categories of this paper are: nucl-th
0
The categories of this paper are: hep-ph
31
The categories of this paper are: ao-sci
27
The categories of this paper are: comp-gas
34
The categories of this paper are: chem-ph
19
The categories of this paper are: eess
33
The categories of this paper are: plasm-ph