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American Journal of Orthodontics and Dentofacial Orthopedics, 2022
This article describes a simple method of applying a time series analysis to sample data sets using a free and open statistical software program, Language R.Records of new patients who visited 2 different university-affiliated orthodontic departments in 2 different countries were collected.
Richard E. Donatelli +3 more
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This article describes a simple method of applying a time series analysis to sample data sets using a free and open statistical software program, Language R.Records of new patients who visited 2 different university-affiliated orthodontic departments in 2 different countries were collected.
Richard E. Donatelli +3 more
+5 more sources
SSRN Electronic Journal, 2006 Any series of observations ordered along a single dimension, such as time, may be thought of as a time series. The emphasis in time series analysis is on studying the dependence among observations at different points in time. What distinguishes time series analysis from general multivariate analysis is precisely the temporal order imposed on the ...
Francis X. Diebold +2 more
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2018
Analysis of epidemic time series is a large endeavor because of the richness of dynamical patterns and plentitude of historical data (Rohani and King 2010). A wide range of tools are used, some of which are borrowed from mainstream statistics other of which are “custom made.” The classic “mainstream” methods belong to two categories: the so-called time-
Abdulkader Aljandali, Motasam Tatahi
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Analysis of epidemic time series is a large endeavor because of the richness of dynamical patterns and plentitude of historical data (Rohani and King 2010). A wide range of tools are used, some of which are borrowed from mainstream statistics other of which are “custom made.” The classic “mainstream” methods belong to two categories: the so-called time-
Abdulkader Aljandali, Motasam Tatahi
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MCN, The American Journal of Maternal/Child Nursing, 1993
Abstract In many biological and medical situations a variable is observed sequentially over a period of time. The resulting set of observations, ordered with respect to time, is called a time series. For example, if the temperature in a certain place is measured at noon on each day for a year, the resulting set of values is a time ...
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Abstract In many biological and medical situations a variable is observed sequentially over a period of time. The resulting set of observations, ordered with respect to time, is called a time series. For example, if the temperature in a certain place is measured at noon on each day for a year, the resulting set of values is a time ...
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2014
A time series is a sequential collection of data indexed over time. In most cases the data are continuous but they are recorded at a discrete and finite set of equally spaced points. If a time series has N-observations (x 0, x 1, …, x N ), then the time indexed distance between any two successive observations is referred to as the sampling interval ...
Asis Kumar Chattopadhyay +1 more
+4 more sources
A time series is a sequential collection of data indexed over time. In most cases the data are continuous but they are recorded at a discrete and finite set of equally spaced points. If a time series has N-observations (x 0, x 1, …, x N ), then the time indexed distance between any two successive observations is referred to as the sampling interval ...
Asis Kumar Chattopadhyay +1 more
+4 more sources
nonlinear time series analysis [PDF]
, 2008 Since the early 1980s, there has been a growing interest in stochastic nonlinear dynamical systems of the form, where is a zero mean, covariance stationary process, is the conditional volatility, and is an independent and identically distributed noise process.
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2009
Abstract This article discusses time-series methods such as simple time-series regressions, ARIMA models, vector autoregression (VAR) models, and unit root and error correction models (ECM). It specifically presents a brief history of time-series analysis before moving to a review of the basic time-series model.
Jon C. W. Pevehouse, Jason D. Brozek
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Abstract This article discusses time-series methods such as simple time-series regressions, ARIMA models, vector autoregression (VAR) models, and unit root and error correction models (ECM). It specifically presents a brief history of time-series analysis before moving to a review of the basic time-series model.
Jon C. W. Pevehouse, Jason D. Brozek
openaire +2 more sources