bluuebunny/crossref_metadata_2025_split huggingface dataset:
Synthesis and characterization of novel biodegradable polymeric prodrugs containing 5‐fluorouracil and 4‐amino‐N‐(2‐pyrimidinyl) benzene sulfonamide terminal groups
Authors: Chang Jun , Du Jie , Zheng Yubin 
Published: May 2007

AbstractTo develop novel biodegradable polymeric prodrugs with target‐directing and drug‐active functional groups, a series of polymeric antitumor prodrugs containing sulfadiazine and 5‐fluorouracil terminal groups were prepared via the two‐step reaction of chlorinated poly(lactic acid) or chlorinated poly(lactic acid‐co‐glycolic acid) with potassium sulfadiazine (SF‐K) and 1,3‐dihydroxymethyl‐5‐fluorouracil. The synthesized polymers were characterized by means of infrared spectroscopy, proton nuclear magnetic resonance spectroscopy, gel permeation chromatography, viscosity measurements, differential scanning calorimetry, and ultraviolet (UV) spectroscopy. The GA/LA value was varied, so that the effects of the comonomer content on the solubility, thermal properties, and degradable behaviors were examined respectively. It was found that introducing the GA units could increase the melting temperature (Tm), the hydrolytic degradation, and the hydrophilicity, while it decreased the glass transition temperature (Tg). The drug content of 5‐FU measured by UV spectra is 56.3 in maximum. © 2007 Wiley Periodicals, Inc. J Appl Polym Sci, 2007
A Method of Estimation of Change Points in Multiphasic Growth Models
Authors: Schulze U. 
Published: May 2007

AbstractThe least‐squares estimation (LSE) of change points and the phase parameters is considered for two growth models with piecewise continuously connected exponential and stationary phases. The calculation of a LSE is reduced to the solution of a finite number of simpler least‐squares problems for which methods of calculation are well known.
Statistical Testing for Seasonality in Data with Multiple Peaks and Troughs
Authors: Marrero O. 
Published: May 2007

AbstractEDWARDS'S test for seasonality is extended to multiple peaks and troughs. It is shown how the extended statistic may be adjusted for the population at risk and for unequal lengths of time intervals in the cycle of seasons. A simulation study shows that the extended test statistic is, for sample sizes N ≧ 100, very specific in detecting the number of peaks and troughs for which it is intended. The associated method of parameter estimation is also assessed; for N ≦ 100, the amplitude of a possibly adequate simple harmonic model is estimated well, but the initial value of the phase angle is not. Estimated percentage points for the extended test statistic are tabulated, and some recommendations are offered regarding usage of this method.
Optimal Fixing of the Bandwidth‐Parameter for the Empirical Regression1,2
Authors: Schmerling S. , Peil J. 
Published: May 2007

AbstractThe estimator ř0(x) of the regression r(x) = E (Y | × = x) from measured points (xi, yi), i = 1(1) n, of a continuous two‐dimensional random variable (X, Y) with unknown continuous density function f(x, y) and with moments up to the second order can be made with the help of a density estimation f̌0(x, y) (see e.g. SCHMERLING and PEIL, 1980). Here f̌0(x, y) still contains free parameters (so‐called band‐width‐parameters), the values of which have to be optimally fixed in the concrete case. This fixing can be done by using a modification of the maximum‐likelihood principle including jackknife techniques. The parameter values can be also found from the estimators for r(x). Here the cross‐validation principle can be applied. Some numerical aspects of these possibilities for optimally fixing the bandwidth‐parameter are discussed by means of examples. If ř0(x) is used as a smoothing operator for time series the optimal choice of the parameter values is dependent on the purpose of application of the smoothed time series. The fixing will then be done by considering the so‐called filter‐characteristic of řC0(x).
Estimation of Covariance Matrices in Unbalanced Random and Mixed Multivariate Models
Authors: Wesolowska‐Janczarek M. T. 
Published: May 2007

AbstractThree HENDERSON'S Methods of estimating the variance components are generalized from one to p variables using a compact matrix notation. These results are obtained using a generalized Kronecker product of matrices, generalized trace of order p and a generalized quadratic form.
Recursive Residuals on a Rectangular Lattice
Authors: Gleeson A. C. , McGilchrist C. A. 
Published: May 2007

AbstractA set of independentN(O, ρ2) recursive residuals is obtained for a model proposed by GLEESON and McGILCHRIST (1980) to describe spatial dependence among observations on a rectangular lattice. These residuals can be used to test model adequacy in a similar fashion to Box‐Jenkins techniques for time series models.
An Analysis of Variance of Nominal Data
Authors: Onukogu I. B. 
Published: May 2007

AbstractThis paper considers a common problem in analysis of variance where the responses to a set of treatments are nominal (i.e. are recorded in frequencies) with no underlying metric. Reasoning by analogy from standard analysis of variance of a two‐way classification we develop chi‐square tests for significance of treatments and interactions. Two tests are proposed for interaction and their asymptotic properties are studied.
Stereological Determination of Orientations, Second‐Order Quantities and Correlations for Random Spatial Fibre Systems
Authors: Stoyan D. 
Published: May 2007

AbstractThis paper presents methods for the stereological analysis of spatial fibre systems on the base of planar or thin sections. Under the assumption that the cross‐section figures of the tubular fibres can be measured, the orientation distribution of the fibre system and its line densityLvcan be determined from one section only and without distributional assumptions.A simple way to study the degree of randomness of fibre systems consists in the statistical analysis of the point pattern of centres of intersection figures. More sophisticated methods are of stereological nature and yield the spatial reduced second moment measure. Similarly also correlations between two fibre systems can be quantified.The methods are demonstrated by two examples concerning samples of human brain.
Use of Growth Indices in Yield Forecast
Authors: Jain R. C. , Agrawal R. , Jha M. P. 
Published: May 2007

AbstractA model has been developed for forecasting of crop yields in which growth indices of biometrical characters based on two or more periods simultaneously have been utilised. The growth indices are obtained as weighted accumulations of observations on biometrical characters in different periods, weights being respective correlation coefficients between yield and biometrical characters. This model has been found better than the models in use.
On the Parametric Approach to Survival Data Analysis I. Radiobiological Applications
Authors: Kadyrova N. O. , Yakovlev A. Yu. 
Published: May 2007

AbstractAcute radiation injury and postirradiation recovery have been formalized in terms of a Markovian homogeneous process of the random walk with a finite set of states, two absorbing barriers and continuous time. The distribution of time for such a process to reach (for the first time) the upper absorbing barrier was earlier obtained by SAATY (1961) and within the proposed model it coincides with the life span distribution for irradiated animals. The possibilities of finding the maximum likelihood estimates of unknown parameters are investigated by means of simulating experiments performed with a computer assistance. On the basis of simulation results the applicability of the proposed distribution for the purposes of survival data analysis is discussed. Extension of the model to accomodate two (or more) radiation syndromes is presented.
Models of Parent‐Offspring Conflict in Small Populations
Authors: Mayo O. , Leach C. R. 
Published: May 2007

AbstractFELDMAN and ESHEL (1982) have introduced a precise two locus genetical model to examine the spread of “selfish” alleles in a genetically “altruistic” population. They have shown that, with complete linkage between the gene affecting “altruism” and another determining parental “interference”, the development of “selfishness” may be prevented. Furthermore, “interference”, may allow the development of “altruism” in a “selfish” population. Small population results illustrate how a deterministic analysis may not provide a satisfactory description of how particular rare events occur. The usefulness of major gene models of this type is discussed.
The Empirical Bayes Classification Rules for Mixtures of Discrete and Continuous Variables
Authors: Wojciechowski T. 
Published: May 2007

AbstractLet us consider a general population π. Each object belonging to the population π is characterized by a pair of correlated random vectors (X, Y). Both X and Y may be mixtures of discrete and continuous random variables. It will be assumed that our population π consists of k groups π1,….,πk, which depend on the value of the random vector Y. A certain object, which is an element of one of the k groups π1, …, πk, has to be classified into the correct group. The knowledge of the value of the random vector Y would permit its correct classification, but the observation of this vector is difficult or dangerous and we must assign the individual on the basis of the observation of the random vector X. The classification procedure is based on randomized decision function δ* which minimizes the risk function i.e. Bayes decision function. We give also two empirical Bayes classification rules i.e. decision functions based on the sample from population π and having property that their risks converge to Bayes risk when the sample size increases.
Numerical Results on Growth Functions
Authors: Berg L. 
Published: May 2007

AbstractTo given values for the weights of twelve rats and the averages of some of them there are fitted different smooth functions by the method of least squares. Piecewise polynomial approximation before and after the turning point suggests via a differential equation an approximation by exponential functions. The composition of these exponential functions leads to an implicit function, which can approximately be substituted by an inverses polynomial. Contrary to the usual growth functions, here the mass of the animals is unbounded, what is adequate to ad libitum feeding supposing immortality. The numerical results are laid down in ten tables and they are provided with comments.
Some Extensions to the Stochastic Study of the Life Table
Authors: Nair T. U. 
Published: May 2007

AbstractThis article discusses the application of statistical techniques in the analysis of the life table. Using a piece‐wise continuous model for the mortality pattern, the maximum likelihood estimates of the probabilities of dying, qi in a life table are obtained. From the form of the covariance matrix it is deduced that the estimates are asymptotically independent. The distribution of qi and its large sample variance are also derived.
A Note on Binary Contingency Tables
Authors: Upton Graham J. G. 
Published: May 2007

AbstractThis paper considers contingency tables in which the marginal frequencies for one variable are all 1. This could occur with two‐category binary data or when a continuous variable is treated in categorical fashion. Some results concerning the expectation of goodness‐of‐fit statistics are reported. In particular it is noted that the expectation of the Pearson statistic is independent of the model being fitted.
Analysis of Profiles Based on Ordinal Classification Functions and Rank Tests
Authors: Haux R. 
Published: May 2007

AbstractIn this article a test for the comparison of K groups of independent profiles is suggested. It is based on rank tests, in which the criterion is obtained by using a suitably chosen ordinal classification function. This function represents a specific view on the profiles. The test, which is easy to use, can be regarded as a generalisation of other well known tests and can be applied within a variety of situations. The relationships to other procedures for the analysis of profiles are described. Some properties are discussed.
Fidelity Estimation for a Hierarchical Classifier
Authors: Hufnagl P. , Voss K. 
Published: May 2007

AbstractTo estimate the correct classification rate of a classifier, many different methods exist (test sample, bootstrap, cross validation). The test sample is a method with very small expense. Sometimes, only a small number of objects is available (seldom diseases, high costs for experiments). When we split the sample in training set and test set, we get good or bad fidelity estimations but, unfortunately, vice versa a big or small confidence interval for the estimation. Overcoming this dilemma is only possible for simple classifiers. Such a simple classifier is investigated and a direct fidelity estimation is proposed.
Selection of the Better of Two Treatments when They May Not be Equivalent
Authors: Desu M. M. , Bristol D. R. 
Published: May 2007

AbstractA procedure for selecting the better of two treatments which allows for the possibility of non‐selection when the treatments appear to be equivalent (that is, similar) is presented. The proposed procedure is a modification of the indifference zone approach. It is assumed that the treatments are compared with respect to a continuous response variable, which has a normal or a two‐parameter exponential distribution. For the normal distribution, each of the parameters is considered as the ranking parameter. For the two‐parameter exponential distribution, the guarantee time (location parameter) is the ranking parameter. The values of the estimates of the ranking parameters and the observed distance between these estimates are used in this selection procedure.
The Exact Distribution of the Anderson‐Kannemann Statistic
Authors: Küchenhoff H. , Lehmacher W. 
Published: May 2007

AbstractThe Anderson‐Kannemann test is a rank test for treatment effects in a randomized block design with K treatments and N blocks. In this paper, an algorithm for computing the exact distribution of the Anderson‐Kannemann test statistic under the null hypothesis is deduced. Then, the exact distribution is compared with the asymptotic χ2‐distribution, and it is shown that the exact distribution is approximated fairly well by the asymptotic distribution. Tables of the exact distribution are given for K = 3, N = 3(1)15; K = 4, N = 3(1)11; K = 5, N = 3(1)7; and K = 6, N = 3(1)5.
Efficient Estimators for the verianoe of a Finite Population
Authors: Kaur P. 
Published: May 2007

AbstractFor the estimation of finite population variance of a character, DAS and TRIPATHI (1978) proposed some efficient estimators when population mean of variance of some other character (associated with main character) is known. We propose here some estimators for population variance using same information and compare with those given by DAS and TRIPATHI (1978). Some examples are given for illustration.
Confidence Estimation of an Unknown Component of the Vector of Regressor Variables in Multivariate Linear Regression
Authors: Rausch W. , Horn M. 
Published: May 2007

AbstractThe model used in this paper is Y = Xβ, where with magnified imageunknown x0. Estimators of x0 are derived by putting βmx0 =βm+1 regarding βm+1 as a new unknown parameter. Formally we use the model Y = X1β+ + e where β′+ = (β0, …βm+1 and magnified image Then βm+1/ βm is a point estimator of x0. Assuming normality for e and taking the random variable z=βmx0−βm+1 we get a t‐distributed variable and finally a confidence estimator of x0.The formulas are applied in dose response relations in antibiotic assays refering to a standard. Now we can take into account not only the dependence on the dose/concentration but also on the position on the test agar plate where the test solution is filled in. As a consequence the confidence interval of the unknown dose/concentration x0 becomes shorter and by it the statements more precise.
The Decompositions for Point Symmetry Models in Two‐way Contingency Tables
Authors: Tomizawa S. 
Published: May 2007

AbstractThe decomposition for the complete point symmetry model in a rectangular contingency table is shown. Also the respective decompositions for the local point symmetry model and the reverse local point symmetry model in a square contingency table are given. Moreover test procedures for the decomposed models and an example are given.
Efficient Estimation of Protein Binding Constants
Authors: Connett J. , Gharrett A. , McHugh R. 
Published: May 2007

AbstractAssays of cyclic AMP typically employ a Scatchard‐like data analysis to estimate the total binding protein RT and the dissociation constant Kd. The linear regression procedure employed is statistically ad hoc because the response variable (bound counts) occurs on both sides of the Scatchard equation.The alternative analysis presented here is derived from the cyclic AMP binding reaction. The resulting data analysis, employing non‐linear least squares, results in estimators that on the basis of Monte Carlo studies have less bias and greater precision than the Scatchard method.
Nonparametric Evaluation of Repeated Measurement Designs by Point‐Symmetry Testing
Authors: Lienert G. A. , Netter Petra 
Published: May 2007

AbstractIt is suggested to use simultaneous point‐symmetry tests in evaluating trivariate repeated measurement designs nonparametrically. With k =3 treatments being applied to each of N individuals in randomized sequence, pairs of treatments are compared as to 3 variables or incremental sign patterns. It is shown that unifold trivariate tests preserve more information than do multifold univariate tests. The method is illustrated by an example from psychophysiological research.
Nonparametric Evaluation of ANOVA Designs by Local, Regional, and Global Contingency Testing
Authors: Havranek T. , Kohnen R. , Lienert G. A. 
Published: May 2007

AbstractNonparametric analysis of ANOVA designs is proposed to be done by simultaneous contingency testing of discretised response variables. Selected treatment‐response patterns are evaluated by predictive configural frequency analysis (local contingency). Treatment response associations are defined by regional contingencies. Total treatment‐response relation is defined by global contingency. All methods are illustrated numerically by biometrical examples.
Parameter Estimation for the Bateman Function via Moments of the Empirical Curve
Authors: Knolle H. 
Published: May 2007

AbstractThe parameters of the function f(t)=c(e−at‐e−bt) are related in a simple way to the moments ∞ tnf(t)dt(n=0, 1, 2). Using empirical values of f, the moments can be estimated by numerical integration. Therefrom estimates of the parameters are obtained by elementary algebra.
A Note on Non‐Parametric Tests for the Interaction in Two‐Way Layouts
Authors: Kubinger Klaus D. 
Published: May 2007

AbstractA suggestion is given of how to prove main and interaction effects in two‐way layouts independent of each other even if the data are just ordinally scaled. Starting from HILDEBRAND'S (1980a, b) non‐parametric approach which presupposes interval‐scaled data, transformations of ranks are settled before analysis per analogy to theH‐test takes place. That is, the same formula of an asymptoticallyX2‐distributed test‐statistic results but mean ranks are used instead of mean scores in order to partialize, for instance, main effects while testing interaction effect. Finally an allusion is given of how to handle ties as well as unequal sample sizes.
Application of the Principal Components Method and the Proportional Hazards Regression Model to Analysis of Survival Data
Authors: Danielyan S. A. , Zharinov G. M. , Osipova T. T. 
Published: May 2007

AbstractOne of factor analysis techniques, viz. the principal components method, and the proportional hazards regression model (Cox, 1972) are applied in this work to study the significance of various factors characterizing the patient, the disease, and the method of treatment in the survival. The application of these methods to analysis of survival data for cervical cancer patients has shown, in particular, the tumor growth rate to be the crucial factor in distribution of the patients survival time and to be even more important than the therapy characteristics.
One Degree of Freedom for Non‐Additivity in a Contingency Table and Its Multivariate Extension
Authors: Onukogu Ike B. 
Published: May 2007

AbstractThe paper develops a chi‐square test with one degree of freedom for row‐column interaction in a contingency table. Use is made of the JOHNSON‐GRAYBILL [1972] model which is herein generalized to a twoway multiple response situation. Some of the merits of the new test over the better‐known tests for the same hypothesis are discussed.
Analysis of Triangular Diallel Table for Experiments in Block Designs
Authors: Ceranka B. , Kielczewska H. 
Published: May 2007

AbstractIn this paper the analysis of genotypes obtained in diallel crossing system, including one set ofF1′sand parents, arranged in triangular table is given. This analysis is presented for data obtained from the experiments laid out in block designs. The analysis of variance, estimators of general and specific combining abilities as well as statistics for testing of hypotheses concerning those parameters are given.
Bayesian Estimation in a Generalized Negative Binomial Distribution
Authors: Islam M. N. , Consul P. C. 
Published: May 2007

AbstractA generalized negative binomial (GNB) distribution was introduced by JAIN and CONSUL (1971) and was modified by NELSON (1975). The probability function of the distribution is defined by the function p(x; m, β, θ)= θx (1 ‐ θ)m+βx—x for x=0, 1, …, and zero otherwise, where m>0, 0<θ<1 and β=0 or 1≦β<θ−1. The Bayes estimators for a number of parametric functions of θ when m and β are known are derived. The prior information on θ may be given by a beta distribution, B(a, b), to which no subjective significance is attached. It has been illustrated that the parameters in the prior distribution can be assigned by a computer. Comparisons are made of the Bayes estimate of P(X=k) to the corresponding ML estimate and the MVU estimate for any given sample to the order n−1 for different values of k..
Weighted Standardization—A General Data Transformation Method Proceeding Classification Procedures
Authors: Hohenegger J. 
Published: May 2007

AbstractDuring preparatory steps of data for automatic classification routines, the amount of information contained by the character distribution is reduced by standardization of the character values. This information can be regained through special weighting schemes of standardized character values. Two weight coefficients derived from decomposition of the frequency distributions of the characters are proposed.
Elementary Analysis of Multidimensional Contingency Tables. Application to a Medical Example1/2
Authors: Enke H. 
Published: May 2007

AbstractBy the aid of analysing a medical example a three—step procedure for analysing multi—dimensional contingency tables is introduced. This procedure has some good properties.Step one is due to catch the relationship structure between the variables connected by the contingency table. Hereby only so—called graphical models, a subclass of hierarchical models in regard of the parameters of the log—linear model, are admitted. The models can be generated by combination of hypotheses of pairwise conditional independence. Hereby a so‐called Extended Combination Procedure is proposed using the position of the Chain of (hierarchical) Hypotheses. A useful symbolic notation for ‘Dependence Models’ in addition to that in form of ‘Independence Models’ and ‘Minimal Sets’ is proposed. Step two analyses the significant conditional pairs in regard to the question for what attribute level combinations of the condition complexes the relations remain significant.Step three investigates those tables recognised as significant in step two more closely to get ideas about the ‘sources’ of dependencies and possibilities of collapsing parts of the table.The procedure is mostly used in explorative data analysis although the simple steps can be used to test hypotheses, too.