Menu-driven X-12-ARIMA seasonal adjustment in Stata

The X-12-ARIMA software of the U.S. Census Bureau is one of the most popular methods for seasonal adjustment; the program x12a.exe is widely used around the world. Some software also provides X-12-ARIMA seasonal adjustments by using x12a.exe as a plug-in or externally. In this article, we illustrate a menu-driven X-12-ARIMA seasonal-adjustment method in Stata. Specifically, the main utilities include how to specify the input file and run the program, how to make a diagnostics table, how to import data, and how to make graphs

Long-run covariance and its applications in cointegration regression

Long-run covariance plays a major role in much of time-series inference, such as heteroskedasticity- and autocorrelation-consistent standard errors, generalized method of moments estimation, and cointegration regression. We propose a Stata command, lrcov, to compute long-run covariance with a prewhitening strategy and various kernel functions. We illustrate how long-run covariance matrix estimation can be used to obtain heteroskedasticity- and autocorrelation-consistent standard errors via the new hacreg command; we also illustrate cointegration regression with the new cointreg command. hacreg has several improvements compared with the official newey command, such as more kernel functions, automatic determination of the lag order, and prewhitening of the data. cointreg enables the estimation of cointegration regression using fully modified ordinary least squares, dynamic ordinary least squares, and canonical cointegration regression methods. We use several classical examples to demonstrate the use of these commands

GPS trajectory agglomeration and refined road network extraction

Aiming at the shortcomings of low-accuracy in the use of GPS data to extract bidirection a roads and intersections, this paper proposes a trajectory agglomeration and refined roads extraction method that takes into account the position and travel direction to extracts refined road network. First,we remove the discrete and abnormal trajectory points from the original trajectory and insert the trajectory points into the trajectory segments by a certain step size, in order to improve the extraction accuracy of the intersection network.Second,we introduce the driving direction angle to express the driving direction of the vehicle at the track point, obtain its similar trajectory points set by considering the position and direction of the track point, calculate the offset distance of each track point in turn, and complete the track aggregation by iteratively offsetting the track points.Finally, we eliminate the track points that have not been successfully gathered, and use the Grid digitization method to extract the road network that can reflect the fine steering relationship of the roads from the trajectory data after gather. The trajectory agglomeration and road network extraction experiments were carried out with GPS data of Fuzhou taxis. The experimental results show that this method can effectively gather the GPS trajectories according to the direction of vehicle travel and the extracted road network is bidirectional roads, and can finely reflect the steering relationship of the roads at the intersections

Characterizing Intercity Mobility Patterns for the Greater Bay Area in China

Understanding intercity mobility patterns is important for future urban planning, in which the intensity of intercity mobility indicates the degree of urban integration development. This study investigates the intercity mobility patterns of the Greater Bay Area (GBA) in China. The proposed workflow starts by analyzing intercity mobility characteristics, proceeds to model the spatial-temporal heterogeneity of intercity mobility structures, and then identifies the intercity mobility patterns. We first conduct a complex network analysis, based on weighted degrees and the PageRank algorithm, to measure intercity mobility characteristics. Next, we calculate the Normalized Levenshtein Distance for Population Mobility Structure (NLPMS) to quantify the differences in intercity mobility structures, and we use the Non-negative Matrix Factorization (NMF) to identify intercity mobility patterns. Our results showed an evident ‘Core-Periphery’ differentiation characterized by intercity mobility, with Guangzhou and Shenzhen as the two core cities. An obvious daily intercity commuting pattern was found between Guangzhou and Foshan, and between Shenzhen and Dongguan cities at working time. This pattern, however, changes during the holidays. This is because people move from the core cities to peripheral cities at the beginning of holidays and return at the end of holidays. This study concludes that Guangzhou and Foshan have formed a relatively stable intercity mobility pattern, and the Shenzhen–Dongguan–Huizhou metropolitan area has been gradually formed

Nonlinear Characteristics of Phillips Curve: The International Evidence from Panel Data

The paper utilizes international panel data of OECD countries during 1971~2007, such as employment rate and inflation rate, etc., to investigate the nonlinear characteristics of the Phillips curve. It is shown that the Phillips curve is not a simple linear relation; instead, there is an obvious nonlinear characteristic. Using the panel threshold model and smooth transition model, it is shown that the relation between inflation rate and unemployment rate changes with the change in inflation rate. The substitution relation between them is very obvious under high inflation, but the obviously weakened and even disappears in low inflation condition

Nine Tiles Model Construction and Cache of CGML in Mobile

Document management is a usual way to organize spatial data in mobile terminals. And the compressed CGML spatial data has been widely used in location based services. Referring to the thoughts of map set in cartography, nine closely connected and equal sized rectangles are used as the scope for requesting mobile map data, and these nine closely connected rectangles are built to be nine tiles model. Therefore, in view of the method of block requesting and storing on mobile spatial data following nine tiles model, as well as the large quantity of mobile spatial data and its complex geometry relation, this paper puts forward the construction mechanism of nine tiles model and cache organization of CGML spatial data in mobile terminals that abide by nine tiles model. This way of organization and management of mobile spatial data is good to increase the efficiency of heavy spatial data accessing in the low band and reliability of wireless network environment

An All-Time-Domain Moving Object Data Model, Location Updating Strategy, and Position Estimation

To solve the problems from the existing moving objects data models, such as modeling spatiotemporal object continuous action, multidimensional representation, and querying sophisticated spatiotemporal position, we firstly established an object-oriented all-time-domain data model for moving objects. The model added dynamic attributes into object-oriented model, which supported all-time-domain data storage and query. Secondly, we proposed a new dynamic threshold location updating strategy. The location updating threshold was given dynamically in accordance with the velocity, accuracy, and azimuth positioning information from the GPS. Thirdly, we presented several different position estimation methods to estimate the historical location and future location. The cubic Hermite interpolation function is used to estimate the historical location. Linear extended positioning method, velocity mean value positioning method, and cubic exponential smoothing positioning method were designed to estimate the future location. We further implemented the model by abstracting the data types of moving object, which was established by PL∖SQL and extended Oracle Spatial. Furthermore, the model was tested through the different moving objects. The experimental results illustrate that the location updating frequency can be effectively reduced, and thus the position information transmission flow and the data storage were reduced without affecting the moving objects trajectory precision

Wireless Localization Based on RSSI Fingerprint Feature Vector

RSSI wireless signal is a reference information that is widely used in indoor positioning. However, due to the wireless multipath influence, the value of the received RSSI will have large fluctuations and cause large distance error when RSSI is fitted to distance. But experimental data showed that, being affected by the combined factors of the environment, the received RSSI feature vector which is formed by lots of RSSI values from different APs is a certain stability. Therefore, the paper proposed RSSI-based fingerprint feature vector algorithm which divides location area into grids, and mobile devices are localized through the similarity matching between the real-time RSSI feature vector and RSSI fingerprint database feature vectors. Test shows that the algorithm can achieve positioning accuracy up to 2–4 meters in a typical indoor environment