"The purpose of this paper is to provide an introductory overview about the making of family provision claims in South Australia under the Inheritance (Family Provision) Act 1972".

Gould, John, 1804-1881. Monograph of the Trochilidae, or family of humming-birds.

Polish people -- Genealogy.

Archival resources -- Great Britain.

Genealogy

Genealogy -- Computer network resources -- Directories.

Law, Benjamin, 1982- -- Family -- Humor.

[1924?]

Dunbar : printed by and for G. Miller, 1817.

[Dublin] : National Art Union for Ireland, [between 1847 and 1851?]

[1905?]

[QLD, Australia] : Hawkeye Publishing, 2018.

Middletown, DE : Amazon, 2018.

Rockville, Maryland : National Institute on Drug Abuse, 1979.

Rockville, Maryland : National Institute on Drug Abuse, 1980.

Hear how former Oregon State guard and current member of the WNBA's LA Sparks Sydney Wiese is recovering from a COVID-19 diagnosis, seeing friends and family show support and love during a trying time.

Michael Schweinberger, Jonathan Stewart.

Source: The Annals of Statistics, Volume 48, Number 1, 374--396.

Abstract:
Statistical inference for exponential-family models of random graphs with dependent edges is challenging. We stress the importance of additional structure and show that additional structure facilitates statistical inference. A simple example of a random graph with additional structure is a random graph with neighborhoods and local dependence within neighborhoods. We develop the first concentration and consistency results for maximum likelihood and $M$-estimators of a wide range of canonical and curved exponential-family models of random graphs with local dependence. All results are nonasymptotic and applicable to random graphs with finite populations of nodes, although asymptotic consistency results can be obtained as well. In addition, we show that additional structure can facilitate subgraph-to-graph estimation, and present concentration results for subgraph-to-graph estimators. As an application, we consider popular curved exponential-family models of random graphs, with local dependence induced by transitivity and parameter vectors whose dimensions depend on the number of nodes.

Michael Schweinberger.

Source: Bernoulli, Volume 26, Number 2, 1205--1233.

Abstract:
We consider the challenging problem of statistical inference for exponential-family random graph models based on a single observation of a random graph with complex dependence. To facilitate statistical inference, we consider random graphs with additional structure in the form of block structure. We have shown elsewhere that when the block structure is known, it facilitates consistency results for $M$-estimators of canonical and curved exponential-family random graph models with complex dependence, such as transitivity. In practice, the block structure is known in some applications (e.g., multilevel networks), but is unknown in others. When the block structure is unknown, the first and foremost question is whether it can be recovered with high probability based on a single observation of a random graph with complex dependence. The main consistency results of the paper show that it is possible to do so under weak dependence and smoothness conditions. These results confirm that exponential-family random graph models with block structure constitute a promising direction of statistical network analysis.

Thomson (Family)

Fuhlbohm (Family)

South East Family History Group (S.A.) -- Periodicals.

Hewish Henry -- Family.

Grant (Family)

Hicks (Family)

Family histories -- South Australia -- Bibliography.

Klemm (Family)

King's Orphan Schools (New Town, Tas.)

Our Lady of Grace School (Glengowrie, S.A.)

Germans -- South Australia.

Rungie (Family)

Fuhlbohm (Family)

Hubbe (Family)

Cook, William, 1815-1897

Sherwell (Family)

Nixon, Geoffrey Owen, 1921-2011.

Jared W. Young
Mar 4, 2009; 29:2663-2665
Journal Club