29,754 research outputs found
Communication Theoretic Data Analytics
Widespread use of the Internet and social networks invokes the generation of
big data, which is proving to be useful in a number of applications. To deal
with explosively growing amounts of data, data analytics has emerged as a
critical technology related to computing, signal processing, and information
networking. In this paper, a formalism is considered in which data is modeled
as a generalized social network and communication theory and information theory
are thereby extended to data analytics. First, the creation of an equalizer to
optimize information transfer between two data variables is considered, and
financial data is used to demonstrate the advantages. Then, an information
coupling approach based on information geometry is applied for dimensionality
reduction, with a pattern recognition example to illustrate the effectiveness.
These initial trials suggest the potential of communication theoretic data
analytics for a wide range of applications.Comment: Published in IEEE Journal on Selected Areas in Communications, Jan.
201
Forecasting Stock Time-Series using Data Approximation and Pattern Sequence Similarity
Time series analysis is the process of building a model using statistical
techniques to represent characteristics of time series data. Processing and
forecasting huge time series data is a challenging task. This paper presents
Approximation and Prediction of Stock Time-series data (APST), which is a two
step approach to predict the direction of change of stock price indices. First,
performs data approximation by using the technique called Multilevel Segment
Mean (MSM). In second phase, prediction is performed for the approximated data
using Euclidian distance and Nearest-Neighbour technique. The computational
cost of data approximation is O(n ni) and computational cost of prediction task
is O(m |NN|). Thus, the accuracy and the time required for prediction in the
proposed method is comparatively efficient than the existing Label Based
Forecasting (LBF) method [1].Comment: 11 page
Investigating international new product diffusion speed: A semiparametric approach
Global marketing managers are interested in understanding the speed of the
new product diffusion process and how the speed has changed in our ever more
technologically advanced and global marketplace. Understanding the process
allows firms to forecast the expected rate of return on their new products and
develop effective marketing strategies. The most recent major study on this
topic [Marketing Science 21 (2002) 97--114] investigated new product diffusions
in the United States. We expand upon that study in three important ways. (1)
Van den Bulte notes that a similar study is needed in the international
context, especially in developing countries. Our study covers four new product
diffusions across 31 developed and developing nations from 1980--2004. Our
sample accounts for about 80% of the global economic output and 60% of the
global population, allowing us to examine more general phenomena. (2) His model
contains the implicit assumption that the diffusion speed parameter is constant
throughout the diffusion life cycle of a product. Recognizing the likely
effects on the speed parameter of recent changes in the marketplace, we model
the parameter as a semiparametric function, allowing it the flexibility to
change over time. (3) We perform a variable selection to determine that the
number of internet users and the consumer price index are strongly associated
with the speed of diffusion.Comment: Published in at http://dx.doi.org/10.1214/11-AOAS519 the Annals of
Applied Statistics (http://www.imstat.org/aoas/) by the Institute of
Mathematical Statistics (http://www.imstat.org
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