scholarly journals R Language: Statistical Computing and Graphics for Modeling Hydrologic Time Series

2014 ◽  
Vol 10 (4) ◽  
pp. 9-18
Author(s):  
Gabriela-Roxana Dobre
Keyword(s):  
Time Series ◽  
Statistical Analysis ◽  
Statistical Model ◽  
Graphical Representation ◽  
Statistical Computing ◽  
R Language ◽  
Hydrologic Time Series ◽  
Time Period ◽  
Precipitation And Temperature ◽  
Representation Of Time

Abstract The analysis and management of Hydrology time series is used for the development of models that allow predictions on future evolutions. After identifying the trends and the seasonal components, a residual analysis can be done to correlate them and make a prediction based on a statistical model. Programming language R contains multiple packages for time series analysis: ‘hydroTSM’ package is adapted to the time series used in Hydrology, package ‘TSA’ is used for general interpolation and statistical analysis, while the ‘forecast’ package includes exponential smoothing, all having outstanding capabilities in the graphical representation of time series. The purpose of this paper is to present some applications in which we use time series of precipitation and temperature from Fagaras in the time period 1966-1982. The data was analyzed and modeled by using the R language.

scholarly journals ANALISIS MULTIRESOLUSI WAVELET DENGAN TRANSFORMASI WAVELET DISKRIT BERBASIS GUI R (STUDI KASUS: INFLASI DI INDONESIA PADA PERIODE OKTOBER 2007-MEI 2018)

2020 ◽  
Vol 9 (2) ◽  
pp. 143-151
Author(s):  
Sania Anisa Farah ◽  
Suparti Suparti ◽  
Dwi Ispriyanti
Keyword(s):  
Time Series ◽  
Statistical Analysis ◽  
Graphical User Interface ◽  
Signal Analysis ◽  
Parametric Method ◽  
Analysis Data ◽  
Statistical Computing ◽  
Discrete Wavelet ◽  
Command Line ◽  
Command Line Interface

Lately, the wavelet applications are widely used in statistics, one of them is discrete wavelet transform (DWT) which is a non-parametric method for signal analysis, data compression, and time series analysis. As technology becomes more advanced, a software is necessary to support the statistical analysis by such method, one of them being the open source based R. It is often used in statistical computing with command line interface (CLI) which requires the R user to remember the names of syntaxes and functions. It becomes less effective when there are many related statistical analysis involved, so graphical user interface (GUI) is needed to access all of them easily. The testing of multiresolution analysis by DWT for Haar, Daublets, and Coiflets filters with levels 1-6 had been performed by using the inflation data in Indonesia during October 2007-May 2018 taken from Bank Indonesia website. The result shows that the sixth level of DWT gives the best estimation for each filters, and Daublets 20 is the best filter for overall estimation with MSE, MAPE, and MASE values are 0.05755, 3.40678, and 0.35343 respectively. The packages for GUI construction in R are wavelets and shiny. Based on its usage, the GUI is capable of processing the chosen analysis and showing the valid output.

An Application of Elman Networks In Treatment and Prediction of Hydrologic Time Series

2011 ◽  
Vol 9 (3) ◽  
pp. 148-156
Author(s):  
Leonardo G. Tampelini ◽  
Clodis Boscarioli ◽  
Sarajane M. Peres ◽  
Silvio C. Sampaio
Keyword(s):  
Time Series ◽  
Hydrologic Time Series

scholarly journals Proposal for Tower Crane Productivity Indicators Based on Data Analysis in the Era of Construction 4.0

Buildings ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 21
Author(s):  
Thomas Danel ◽  
Zoubeir Lafhaj ◽  
Anand Puppala ◽  
Sophie Lienard ◽  
Philippe Richard
Keyword(s):  
Time Series ◽  
Data Analysis ◽  
Statistical Analysis ◽  
Data Collection ◽  
Structural Phase ◽  
Sampling Technique ◽  
Construction Site ◽  
Data Logger ◽  
Tower Crane ◽  
Productivity Indicators

This article proposes a methodology to measure the productivity of a construction site through the analysis of tower crane data. These data were obtained from a data logger that records a time series of spatial and load data from the lifting machine during the structural phase of a construction project. The first step was data collection, followed by preparation, which consisted of formatting and cleaning the dataset. Then, a visualization step identified which data was the most meaningful for the practitioners. From that, the activity of the tower crane was measured by extracting effective lifting operations using the load signal essentially. Having used such a sampling technique allows statistical analysis on the duration, load, and curvilinear distance of every extracted lifting operation. The build statistical distribution and indicators were finally used to compare construction site productivity.

scholarly journals Shift Detection in Hydrological Regimes and Pluriannual Low-Frequency Streamflow Forecasting Using the Hidden Markov Model

Water ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 2058 ◽  
Author(s):  
Larissa Rolim ◽  
Francisco de Souza Filho
Keyword(s):  
Time Series ◽  
Markov Model ◽  
Hidden Markov Model ◽  
Extreme Events ◽  
Hidden Markov ◽  
Low Frequency ◽  
Streamflow Forecasting ◽  
Hydrologic Time Series ◽  
Low Frequency Variability ◽  
The Impact

Improved water resource management relies on accurate analyses of the past dynamics of hydrological variables. The presence of low-frequency structures in hydrologic time series is an important feature. It can modify the probability of extreme events occurring in different time scales, which makes the risk associated with extreme events dynamic, changing from one decade to another. This article proposes a methodology capable of dynamically detecting and predicting low-frequency streamflow (16–32 years), which presented significance in the wavelet power spectrum. The Standardized Runoff Index (SRI), the Pruned Exact Linear Time (PELT) algorithm, the breaks for additive seasonal and trend (BFAST) method, and the hidden Markov model (HMM) were used to identify the shifts in low frequency. The HMM was also used to forecast the low frequency. As part of the results, the regime shifts detected by the BFAST approach are not entirely consistent with results from the other methods. A common shift occurs in the mid-1980s and can be attributed to the construction of the reservoir. Climate variability modulates the streamflow low-frequency variability, and anthropogenic activities and climate change can modify this modulation. The identification of shifts reveals the impact of low frequency in the streamflow time series, showing that the low-frequency variability conditions the flows of a given year.

scholarly journals A periodic and seasonal statistical model for non-negative integer-valued time series with an application to dispensed medications in respiratory diseases

2021 ◽  
Vol 96 ◽  
pp. 545-558
Author(s):  
Paulo Roberto Prezotti Filho ◽  
Valderio Anselmo Reisen ◽  
Pascal Bondon ◽  
Márton Ispány ◽  
Milena Machado Melo ◽  
...  
Keyword(s):  
Time Series ◽  
Statistical Model ◽  
Respiratory Diseases ◽  
Negative Integer

scholarly journals Complexity traits and synchrony of cryptocurrencies price dynamics

2021 ◽  
Author(s):  
Davide Provenzano ◽  
Rodolfo Baggio
Keyword(s):  
Time Series ◽  
Complex Network ◽  
Complex Structures ◽  
Slope Parameter ◽  
Exponential Distributions ◽  
Horizontal Visibility ◽  
Time Period ◽  
Before And After ◽  
Visibility Algorithm ◽  
Similar Complex

AbstractIn this study, we characterized the dynamics and analyzed the degree of synchronization of the time series of daily closing prices and volumes in US$ of three cryptocurrencies, Bitcoin, Ethereum, and Litecoin, over the period September 1,2015–March 31, 2020. Time series were first mapped into a complex network by the horizontal visibility algorithm in order to revel the structure of their temporal characters and dynamics. Then, the synchrony of the time series was investigated to determine the possibility that the cryptocurrencies under study co-bubble simultaneously. Findings reveal similar complex structures for the three virtual currencies in terms of number and internal composition of communities. To the aim of our analysis, such result proves that price and volume dynamics of the cryptocurrencies were characterized by cyclical patterns of similar wavelength and amplitude over the time period considered. Yet, the value of the slope parameter associated with the exponential distributions fitted to the data suggests a higher stability and predictability for Bitcoin and Litecoin than for Ethereum. The study of synchrony between the time series investigated displayed a different degree of synchronization between the three cryptocurrencies before and after a collapse event. These results could be of interest for investors who might prefer to switch from one cryptocurrency to another to exploit the potential opportunities of profit generated by the dynamics of price and volumes in the market of virtual currencies.

Free Traders and Drug Smugglers: The Effects of Trade Openness on States' Ability to Combat Drug Trafficking

2009 ◽  
Vol 51 (2) ◽  
pp. 117-145 ◽  
Author(s):  
Horace A. Bartilow ◽  
Kihong Eom
Keyword(s):  
Time Series ◽  
Statistical Model ◽  
Drug Trafficking ◽  
Trade Openness ◽  
Cross Sectional ◽  
Theoretical Literature ◽  
Openness To Trade ◽  
Pooled Time Series

AbstractThe theoretical literature presents conflicting expectations about the effects of trade openness on the ability of states to interdict drug trafficking. One view expects that trade openness will undermine drug interdiction; a second argues the opposite; a third argues that trade openness does not necessarily affect drug interdiction. This article assesses empirically the effects of trade openness on drug interdiction for countries in the Americas using a pooled time-series cross-sectional statistical model. It finds that trade openness decreases the interdiction capabilities of states in drug-consuming countries while increasing those of states in drug-producing countries. Greater openness to trade does not have a consistently significant effect on the interdiction capabilities of states in drug transit countries.

Sign in / Sign up

Export Citation Format

Share Document