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Our population statistics cover age, sex, race, Hispanic origin, migration, ancestry, language use, veterans, as well as population estimates and projections.
This section provides information on a range of educational topics, from educational attainment and school enrollment to school districts, costs and financing.
We measure the state of the nations workforce, including employment and unemployment levels, weeks and hours worked, occupations, and commuting.
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Health statistics on insurance coverage, disability, fertility and other health issues are increasingly important in measuring the nation's overall well-being.
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The U.S. Census Bureau is the official source for U.S. export and import statistics and regulations governing the reporting of exports from the U.S.
The U.S. Census Bureau provides data for the Federal, state and local governments as well as voting, redistricting, apportionment and congressional affairs.
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Geography provides the framework for Census Bureau survey design, sample selection, data collection, tabulation, and dissemination.
Geography is central to the work of the Bureau, providing the framework for survey design, sample selection, data collection, tabulation, and dissemination.
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The Geographic Support System Initiative will integrate improved address coverage, spatial feature updates, and enhanced quality assessment and measurement.
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Metropolitan and micropolitan areas are geographic entities used by Federal statistical agencies in collecting, tabulating, and publishing Federal statistics.
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Definitions of geographic terms, why geographic areas are defined, and how the Census Bureau defines geographic areas.
We conduct research on geographic topics such as how to define geographic areas and how geography changes over time.
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Official audio files from the Census Bureau, including "Profile America," a daily series of bite-sized statistics, placing current data in a historical context.
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Developer portal to access services and documentation for the Census Bureau's APIs.
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Our researchers explore innovative ways to conduct surveys, increase respondent participation, reduce costs, and improve accuracy.
Our surveys provide periodic and comprehensive statistics about the nation, critical for government programs, policies, and decisionmaking.
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Explore the rich historical background of an organization with roots almost as old as the nation.
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The Census Bureau's Director writes on how we measure America's people, places and economy.
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Profile America is a daily, 60-second feature that uses interesting vignettes for that day to highlight information collected by the Census Bureau.
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Trend extraction is one of the major tasks of time series analysis. The trend of a time series is considered as a smooth additive component that contains information about global change. This paper presents a review of some modern approaches to trend extraction for one-dimensional time series. We do not aim to review all the novel approaches, but rather to observe the problem from different viewpoints and from different areas of expertise. The paper contributes to understanding the concept of a trend and the problem of its extraction. We present an overview of advantages and disadvantages of the approaches under consideration, which are: the Model-Based Approach, nonparametric linear filtering, Singular Spectrum Analysis, and wavelets. The Model-Based Approach assumes the specification of a stochastic time series model for the trend, which is usually either and ARIMA model or a state space model. The nonparametric filtering methods (i.e., the Henderson, LOESS, and Hodrick-Prescott filters) do not require specification of a model; they are quite easy to apply and are used in all applied areas of time series analysis. For these well-known methods we show how their properties can be improved by exploiting Reproducing Kernel Hilbert Space methodology. In addition to these extremely popular approaches, we consider Singular Spectrum Analysis (SSA) and wavelet-based methods. Singular Spectrum Analysis is widespread in the geosciences; its algorithm is similar to that of Principal Components Analysis, but SSA is applied to time series. Wavelet-based methods are currently a de facto standard for denoising in many fields. We summarize how the powerful wavelets approach can be used for trend extraction.
Model-based approach; Nonparametric linear filtering; Singular spectrum analysis; Time series; Trend; Wavelets
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