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LEADER 00000nam a2200529Ia 4500 
003    MiAaPQ 
006    m     o  d |       
007    cr cn||||||||| 
008    101001s2011    njua    sb    001 0 eng d 
010    |z2010040947 
019    EBC693526 
019    ebr10466739 
020    |z9780470924198 
035    (MiAaPQ)EBC693526 
035    (Au-PeEL)EBL693526 
035    (CaPaEBR)ebr10466739 
035    (CaONFJC)MIL309865 
035    (OCoLC)729724620 
035    .b42940941 
040    MiAaPQ|beng|cMiAaPQ|dMiAaPQ 
050  4 T57.74|b.M98 2011 
082 04 519.7/2|222 
100 1  Mynbaev, K. T.|q(Kaĭrat Turysbekovich)|0
245 10 Short-memory linear processes and econometric applications
       /|cKairat T. Mynbaev. 
264  1 Hoboken, N.J. :|bWiley,|c2011. 
300    xix, 429 pages :|billustrations 
336    text|btxt|2rdacontent 
337    computer|bc|2rdamedia 
338    online resource|bcr|2rdacarrier 
340    |gpolychrome|2rdacc|0
347    text file|2rdaft|0
504    Includes bibliographical references and index. 
505 00 |g1|tIntroduction to Operators, Probabilities and The 
       Linear Model|g1 --|g1.1|tLinear Spaces|g1 --|g1.2|tNormed 
       Spaces|g3 --|g1.3|tLinear Operators|g6 --|g1.4|tHilbert 
       Spaces|g9 --|g1.5|tL<sub>p</sub> Spaces|g13 --|g1.6
       |tConditioning on σ-fields|g18 --|g1.7|tMatrix Algebra|g21
       --|g1.8|tConvergence of Random Variables|g24 --|g1.9
       |tLinear Model|g29 --|g1.10|tNormalization of Regressors
       |g32 --|g1.11|tGeneral Framework in the case of K 
       Regressors|g35 --|g1.12|tIntroduction to L₂-
       Approximability|g40 --|g2|tLp-Approximable Sequences of 
       Vectors|g45 --|g2.1|tDiscretization, Interpolation and 
       Haar Projector in L<sub>p</sub>|g45 --|g2.2|tConvergence 
       of Bilinear Forms|g49 --|g2.3|tTrinity and Its Boundedness
       in L<sub>p</sub>|g54 --|g2.4|tConvergence of the Trinity 
       on L<sub>p</sub>-Generated Sequences|g57 --|g2.5
       |tProperties of L<sub>p</sub>-Approximable Sequences|g68 -
       -|g2.6|tCriterion of L<sub>p</sub>-Approximability|g71 --
       |g2.7|tExamples and Counterexamples|g80 --|g3|tConvergence
       of Linear and Quadratic Forms|g89 --|g3.1|tGeneral 
       Information|g89 --|g3.2|tWeak Laws of Large Numbers|g93 --
       |g3.3|tCentral Limit Theorems for Martingale Differences
       |g94 --|g3.4|tCentral Limit Theorems for Weighted Sums of 
       Martingale Differences|g95 --|g3.5|tCentral Limit Theorems
       for Weighted Sums of Linear Processes|g102 --|g3.6|tL<sub>
       p</sub>-Approximable Sequences of Matrices|g106 --|g3.7
       |tIntegral operators|g111 --|g3.8|tClasses σ<sub>p</sub>
       |g117 --|g3.9|tConvergence of Quadratic Forms of Random 
       Variables|g122 --|g4|tRegressions with Slowly Varying 
       Regressors|g131 --|g4.1|tSlowly Varying Functions|g132 --
       |g4.2|tPhillips Gallery|g133 --|g4.3|tSlowly Varying 
       Functions with Remainder|g143 --|g4.4|tResults Based on L<
       sub>p</sub>-Approximability|g149 --|g4.5|tPhillips Gallery
       2|g159 --|g4.6|tRegression with Two Slowly Varying 
       Regressors|g174 --|g5|tSpatial Models|g189 --|g5.1|tA Math
       Introduction to Purely Spatial Models|g190 --|g5.2
       |tContinuity of Nonlinear Matrix Functions|g193 --|g5.3
       |tAssumption on the Error Term and Implications|g195 --
       |g5.4|tAssumption on the Spatial Matrices and Implications
       |g198 --|g5.5|tAssumption on the Kernel and Implications
       |g201 --|g5.6|tLinear and Quadratic Forms Involving 
       Segments of K|g205 --|g5.7|tRoundabout Road|g207 --|g5.8
       |tAemptotics of the OLS Estimator for Purely Spatial Model
       |g213 --|g5.9|tMethod of Moments and Maximum Likelihood
       |g217 --|g5.10|tTwo-Step Procedure|g223 --|g5.11|tExamples
       and Computer Simulation|g230 --|g5.12|tMixed Spatial Model
       |g236 --|g5.13|tRoundabout Road (Mixed Model)|g244 --
       |g5.14|tAsymptotic of the OLS Estimator for Mixed Spatial 
       Model|g254 --|g6|tConvergence Almost Everywhere|g265 --
       |g6.1|tTheoretical Background|g265 --|g6.2|tVarious Bounds
       on Martingale Transforms|g270 --|g6.3|tMarcinkiewicz-
       Zygmund Theorems and Related Results|g278 --|g6.4|tStrong 
       Consistency for Multiple Regression|g292 --|g6.5|tSoftie 
       Algebra Related to Vector Autoregression|g300 --|g6.6
       |tPreliminary Analysis|g310 --|g6.7|tStrong Consistency 
       for Vector Autoregression and Related Results|g319 --|g7
       |tNon-Linear Models|g339 --|g7.1|tAttemptotic Normality of
       an Abstract Estimator|g339 --|g7.2|tConvergence of Some 
       Deterministic and Stochastic Expressions|g346 --|g7.3|tNon
       -linear Least Squares|g358 --|g7.4|tBarry Logit Models 
       with Unbounded Explanatory Variables|g373 --|g8|tTools for
       Vector Autoregressions|g393 --|g8.1|tL<sub>p</sub>-
       Approximable Sequences of Matrix-Valued Functions|g393 --
       |g8.2|tT-Operator and Trinity|g397 --|g8.3|tMatrix 
       Operations and L<sub>p</sub>-Approximability|g400 --|g8.4
       |tResolvents|g402 --|g8.5|tConvergence and Bounds for 
       Deterministic Trends|g404. 
533    Electronic reproduction. Ann Arbor, MI : ProQuest, 2015. 
       Available via World Wide Web. Access may be limited to 
       ProQuest affiliated libraries. 
650  0 Linear programming.|0
650  0 Econometric models.|0
650  0 Regression analysis.|0
650  0 Probabilities.|0
655  4 Electronic books. 
710 2  ProQuest (Firm)|0
856 40 |u
       detail.action?docID=693526|zConnect to ebook (University 
       of Melbourne only) 
907    .b42940941 
990    MARCIVE MELB 201906 
990    ProQuest EBL purchased 
990    Batch Ebook load (bud2) - do not edit, delete or attach 
       any records. 
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