A General Completeness Theorem in Sampling Theory

Tzen-Ping Liu
Yonina C. Eldar

2010 ◽  
Vol 12 (3) ◽  
pp. 358-364 ◽  
Liling GAO ◽  
Xinhu LI ◽  
Cuiping WANG ◽  
Quanyi QIU ◽  
Shenghui CUI ◽  

1992 ◽  
Richard Statman ◽  
Gilles Dowek

David Hankin ◽  
Michael S. Mohr ◽  
Kenneth B. Newman

We present a rigorous but understandable introduction to the field of sampling theory for ecologists and natural resource scientists. Sampling theory concerns itself with development of procedures for random selection of a subset of units, a sample, from a larger finite population, and with how to best use sample data to make scientifically and statistically sound inferences about the population as a whole. The inferences fall into two broad categories: (a) estimation of simple descriptive population parameters, such as means, totals, or proportions, for variables of interest, and (b) estimation of uncertainty associated with estimated parameter values. Although the targets of estimation are few and simple, estimates of means, totals, or proportions see important and often controversial uses in management of natural resources and in fundamental ecological research, but few ecologists or natural resource scientists have formal training in sampling theory. We emphasize the classical design-based approach to sampling in which variable values associated with units are regarded as fixed and uncertainty of estimation arises via various randomization strategies that may be used to select samples. In addition to covering standard topics such as simple random, systematic, cluster, unequal probability (stressing the generality of Horvitz–Thompson estimation), multi-stage, and multi-phase sampling, we also consider adaptive sampling, spatially balanced sampling, and sampling through time, three areas of special importance for ecologists and natural resource scientists. The text is directed to undergraduate seniors, graduate students, and practicing professionals. Problems emphasize application of the theory and R programming in ecological and natural resource settings.

1981 ◽  
Vol 4 (4) ◽  
pp. 975-995
Andrzej Szałas

A language is considered in which the reader can express such properties of block-structured programs with recursive functions as correctness and partial correctness. The semantics of this language is fully described by a set of schemes of axioms and inference rules. The completeness theorem and the soundness theorem for this axiomatization are proved.

1981 ◽  
Vol 4 (3) ◽  
pp. 675-760
Grażyna Mirkowska

The aim of propositional algorithmic logic is to investigate the properties of program connectives. Complete axiomatic systems for deterministic as well as for nondeterministic interpretations of program variables are presented. They constitute basic sets of tools useful in the practice of proving the properties of program schemes. Propositional theories of data structures, e.g. the arithmetic of natural numbers and stacks, are constructed. This shows that in many aspects PAL is close to first-order algorithmic logic. Tautologies of PAL become tautologies of algorithmic logic after replacing program variables by programs and propositional variables by formulas. Another corollary to the completeness theorem asserts that it is possible to eliminate nondeterministic program variables and replace them by schemes with deterministic atoms.

1981 ◽  
Vol 4 (1) ◽  
pp. 151-172
Pierangelo Miglioli ◽  
Mario Ornaghi

The aim of this paper is to provide a general explanation of the “algorithmic content” of proofs, according to a point of view adequate to computer science. Differently from the more usual attitude of program synthesis, where the “algorithmic content” is captured by translating proofs into standard algorithmic languages, here we propose a “direct” interpretation of “proofs as programs”. To do this, a clear explanation is needed of what is to be meant by “proof-execution”, a concept which must generalize the usual “program-execution”. In the first part of the paper we discuss the general conditions to be satisfied by the executions of proofs and consider, as a first example of proof-execution, Prawitz’s normalization. According to our analysis, simple normalization is not fully adequate to the goals of the theory of programs: so, in the second section we present an execution-procedure based on ideas more oriented to computer science than Prawitz’s. We provide a soundness theorem which states that our executions satisfy an appropriate adequacy condition, and discuss the sense according to which our “proof-algorithms” inherently involve parallelism and non determinism. The Properties of our computation model are analyzed and also a completeness theorem involving a notion of “uniform evaluation” of open formulas is stated. Finally, an “algorithmic completeness” theorem is given, which essentially states that every flow-chart program proved to be totally correct can be simulated by an appropriate “purely logical proof”.

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