In some applications, we require a monotone estimate of a regression function. In others, we want to test whether the regression function is monotone. For solving the first problem, Ramsay's, Kelly and Rice's, as well as point-wise monotone regression functions in a spline space are discussed and their properties developed. Three monotone estimates are defined: least-square regression splines, smoothing splines and binomial regression splines. The three estimates depend upon a "smoothing parameter": the number and location of knots in regression splines and the usual [formula omitted] in smoothing splines. Two standard techniques for choosing the smoothing parameter, GCV and AIC, are modified for monotone estimation, for the normal errors case. For answering the second question, a test statistic is proposed and its null distribution conjectured. Simulations are carried out to check the conjecture. These techniques are applied to two data sets. / Science, Faculty of / Statistics, Department of / Graduate

Alon 和Krivelevich (SIAM J. Discrete Math. 15(2): 211-227 (2002)) 證明了如果一個圖是ε -非二部圖，那麼階數為Ỡ(1/ε) 的隨機導出于圖以很大概率是非二部圖。我們進一步猜想，這個導出子圖以很大概率是Ω(ε)-非二部圖。Gonen 和Ron (RANDOM 2007) 證明了當圖的最大度不超過O (εn )時猜想成立。我們將對更一般的情形給出證明，對於任意d，所有d 正則(或幾乎d 正則)的圖猜想成立。 / 假設猜想成立的情況下，我們證明二分屬性是可以被單側誤差在O(1/ε^c ) 時間內檢驗的，其中c 是一個嚴格小於2 的常數，而這個結果也改進了Alon 和Krivelevich 的檢驗算法。由於己知對二分屬性的非適應性的檢驗算法需要Ω(1 /ε²) 的複雜性(Bogdanov 和Trevisan ， CCC 2004) ，我們的結果也得出，假設猜想成立，適應性對檢驗二分屬性是有幫助的。 / 另外一個有很多屬性檢驗問題被廣泛研究的領域是布爾函數。對布爾函數單調性的檢驗也是屬性檢驗的經典問題。給定對布爾函數f: {0,1}{U+207F} → {0,1} 的訪問，在[18]中，證明了檢驗算法複雜性的下界是Ω(√n) 。另一方面，在[21]中，作者們構造了一個複雜性為O(n) 的算法。在本文中，我們刻畫一些單調布爾函數的本質，設計算法并分析其對於一些困難例子的效果。最近，在[14] 中， 一個類似的算法被證明是非適應性，單側誤差，複雜性為Ỡ (n⁵/⁶ ε⁻⁵/³) 的算法。 / Alon and Krivelevich (SIAM J. Discrete Math. 15(2): 211-227 (2002)) show that if a graph is ε-far from bipartite, then the subgraph induced by a random subset of Ỡ (1/ε) vertices is not bipartite with high probability. We conjecture that the induced subgraph is Ω(ε)-far from bipartite with high probability. Gonen and Ron (RANDOM 2007) proved this conjecture in the case when the degrees of all vertices are at most O(εn). We give a more general proof that works for any d-regular (or almost d-regular) graph for arbitrary degree d. / Assuming this conjecture, we prove that bipartiteness is testable with one-sided error in time O(1=ε{U+1D9C}), where c is a constant strictly smaller than two, improving upon the tester of Alon and Krivelevich. As it is known that non-adaptive testers for bipartiteness require Ω(1/ε²) queries (Bogdanov and Trevisan, CCC2004), our result shows, assuming the conjecture, that adaptivity helps in testing bipartiteness. / The other area in which various properties have been well studied is boolean function. Testing monotonicity of Boolean functions is a classical question in property testing. Given oracle access to a Boolean function f : {0, 1}{U+207F} →{0, 1}, in [18], it is shown a lower bound of testing is Ω(√n). On the other hand, in [21], the authors introduced an algorithm to test monotonicity using O(n) queries. In this paper, we characterize some nature of monotone functions, design a tester and analyze the performance on some generalizations of the hard case. Recently, in [14], a similar tester is shown to be a non-adaptive, one-sided error tester making Ỡ (n⁵/⁶ ε⁻⁵/³) queries. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Li, Fan. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2013. / Includes bibliographical references (leaves 76-79). / Abstracts also in Chinese. / Abstract --- p.i / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Property Testing --- p.1 / Chapter 1.2 --- Testing Bipartiteness --- p.4 / Chapter 1.3 --- Testing Monotonicity --- p.7 / Chapter 2 --- Testing Bipartiteness --- p.11 / Chapter 2.1 --- Background --- p.11 / Chapter 2.1.1 --- Our result --- p.11 / Chapter 2.1.2 --- The algorithms of Gonen and Ron --- p.13 / Chapter 2.1.3 --- Our proof --- p.16 / Chapter 2.1.4 --- Notation --- p.19 / Chapter 2.2 --- Splitting the vertices by degree --- p.19 / Chapter 2.3 --- The algorithm for high degree vertices --- p.20 / Chapter 2.4 --- Eliminating the high degree vertices --- p.22 / Chapter 2.5 --- From an XOR game to a bipartite graph --- p.33 / Chapter 2.6 --- Proof of the main theorem --- p.35 / Chapter 2.7 --- Proof of the conjecture for regular graphs --- p.37 / Chapter 3 --- Testing Monotonicity --- p.40 / Chapter 3.1 --- Towards an improved tester --- p.40 / Chapter 3.1.1 --- Properties of Distribution D --- p.42 / Chapter 3.1.2 --- An Alternative Representation of D --- p.46 / Chapter 3.1.3 --- Performance of D on Decreasing Functions --- p.51 / Chapter 3.1.4 --- Functions Containing Ω(2{U+207F}) Disjoint Violating Edges --- p.54 / Chapter 3.2 --- A o(n) Monotonicity Tester [14] and Some Improvements --- p.62 / Chapter 3.2.1 --- A o(n) Monotonicity Tester [14] --- p.62 / Chapter 3.2.2 --- An Alternative Proof of Theorem 3.2.2 --- p.65 / Chapter 4 --- Other Related Results --- p.67 / Chapter 4.1 --- Short Odd Cycles in Graphs that are Far From Bipartiteness --- p.67 / Chapter 4.2 --- Fourier Analysis on Boolean Functions --- p.69 / Bibliography --- p.76

Thesis (Ph.D.)--Memorial University of Newfoundland, 2001. / Restricted until November 2003. Bibliography: leaves 170-178.

Thesis (Ph. D.)--Industrial & Systems Engineering, Georgia Institute of Technology, 2005. / Barnes, Earl, Committee Member ; Shapiro, Alex, Committee Member ; Realff, Matthew, Committee Member ; Al-Khayyal, Faiz, Committee Chair ; Ahmed, Shabbir, Committee Co-Chair. Includes bibliographical references.

Thesis (M.S.)--Duquesne University, 2005. / Title from document title page. Abstract included in electronic submission form. Includes bibliographical references (p. 21) and index.

Thesis (Ph. D.)--State University of New York at Buffalo, 2002. / Includes bibliographical references (p. 167-186). Also available in print.

Thesis (M.S.)--University of Nevada, Reno, 2008. / "May, 2008." Includes bibliographical references (leaves 63-64). Online version available on the World Wide Web.

Thesis (Ph. D.)--Ohio State University, 2007. / Title from first page of PDF file. Includes bibliographical references (p. 116-120).

This thesis examines several problems related to singly-constrained Monotropic Network Flow Problems. In the first part, a linear time algorithm that reduces the solution of a monotropic network flow problem with an additional linear equality constraint to the solution of lower dimensional subproblems is presented. Of the subproblems, at most one is a singly-constrained monotropic network flow problem while the others are unconstrained. If none of the subproblems is constrained, the algorithm provides a linear-time transformation of constrained to unconstrained monotropic network flow problems. Extensions to nonlinear and inequality constraints are given. In the second part the qualitative theory of sensitivity analysis for Unconstrained Minimum-Cost Flow Problems presented by Granot and Veinott [GV85] is extended to Minimum-Cost Flow Problems with one additional linear constraint. The departure from the unconstrained network structure is shown to have a profound effect on computational issues. Two natural extensions of the "less-dependent-on" partial ordering of the arcs given in [GV85] are presented. One is decidable in linear time while the other yields more information but is NP-complete in general. The Ripple Theorem gives upper bounds on the absolute value of optimal-flow variations as a function of variations in the problem parameter. Moreover, it shows how changes may "ripple down" throughout the network, decreasing in magnitude as one gets "further away" from the arc whose parameter initiated the change. The Theory of Substitutes and Complements presents necessary and sufficient conditions for optimal-flow changes to consistently have the same (or the opposite) sign in two given arcs. The complexity of determining Substitutes and Complements is shown to be NP-complete in general. However, for all intractable problems, families of cases arise from easily recognizable graph structures and can be computed in linear time. The Monotonicity Theory links the changes in the value of the parameters to the change in the optimal arc-flows. Bounds on the rates of changes are discussed. We further provide a number of practical situations where our theory may apply. We discuss some Multi-Period Multi-Product Inventory-Production models that can be formulated as nonlinear parametric network flow problems with one additional linear constraint. We then apply our theory to help decision makers understand qualitatively how to respond to changes in the environment such as machine breakdown, strike or variations in inventory carrying costs without additional computation. In a second example, we show how a Cash-Flow Management model can be formulated as a nonlinear parametric network flow problem with one additional linear constraint. The theory is then recommended as a method by which a decision maker could understand qualitatively how to respond to changes in the environment such as variations in interest rates, taxes or asset prices without any additional computation. / Business, Sauder School of / Graduate

We study two classes of problems within sublinear algorithms: data structures for approximate nearest neighbor search, and property testing of Boolean functions. We develop algorithmic and analytical tools for proving upper and lower bounds on the complexity of these problems, and obtain the following results: * We give data structures for approximate nearest neighbor search achieving state-of-the-art approximations for various high-dimensional normed spaces. For example, our data structure for 𝘢𝘳𝘣𝘪𝘵𝘳𝘢𝘳𝘺 normed spaces over R𝘥 answers queries in sublinear time while using nearly linear space and achieves approximation which is sub-polynomial in the dimension. * We prove query complexity lower bounds for property testing of three fundamental properties: 𝘬-juntas, monotonicity, and unateness. Our lower bounds for non-adaptive junta testing and adaptive unateness testing are nearly optimal, and the lower bound for adaptive monotonicity testing is the best that is currently known. * We give an algorithm for testing unateness with nearly optimal query complexity. The algorithm is crucially adaptive and based on a novel analysis of binary search over long paths of the hypercube.