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- D Markovic, C Gros
- 2009

A class of models describing the flow of information within networks via routing processes is proposed and investigated, concentrating on the effects of memory traces on the global properties. The long-term flow of information is governed by cyclic attractors, allowing to define a measure for the information centrality of a vertex given by the number of… (More)

The inverse Weibull model was developed by Erto [10]. In practice, the unknown parameters of the appropriate inverse Weibull density are not known and must be estimated from a random sample. Estimation of its parameters has been approached in the literature by various techniques, because a standard maximum likelihood estimate does not exist. To estimate the… (More)

- Dragan Jukic, Darija Markovic
- Applied Mathematics and Computation
- 2010

- Darija Markovic, Dragan Jukic
- Applied Mathematics and Computer Science
- 2013

The Bass model is one of the most well-known and widely used first-purchase diffusion models in marketing research. Estimation of its parameters has been approached in the literature by various techniques. In this paper, we consider the parameter estimation approach for the Bass model based on the nonlinear weighted least squares fitting of its derivative… (More)

- Darija Marković, Luka Borozan
- 2015

Two-parameter growth models of exponential type f (t;a,b) = g(t)exp(a+bh(t)), where a and b are unknown parameters and g and h are some known functions, are frequently employed in many different areas such as biology, finance, statistic, medicine, ect. The unknown parameters must be estimated from the data (wi, ti,yi), i = 1, . . . ,n, where ti denote the… (More)

In this paper we consider nonlinear least squares fitting of the three-parameter inverse Weibull distribution to the given data (wi, ti, yi), i = 1, . . . , n, n ≥ 3. As the main result, we show that the least squares estimate exists provided that the data satisfy just the following two natural conditions: (i) 0 < t1 < t2 < . . . < tn and (ii) 0 < y1 < y2 <… (More)

- Darija Marković
- 2016

Abstract. For the given data (wi, xi, yi), i = 1, . . . , n, and the given model function f(x;θ), where θ is a vector of unknown parameters, the goal of regression analysis is to obtain estimator θ∗ of the unknown parameters θ such that the vector of residuals is minimized in some sense. The common approach to this problem of minimization is the… (More)

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